Orthogonality of sensory and contextual categorical dynamics embedded in a continuum of responses from the second somatosensory cortex.

How does the brain simultaneously process signals that bring complementary information, like raw sensory signals and their transformed counterparts, without any disruptive interference? Contemporary research underscores the brain's adeptness in using decorrelated responses to reduce such interference. Both neurophysiological findings and artificial neural networks support the notion of orthogonal representation for signal differentiation and parallel processing. Yet, where, and how raw sensory signals are transformed into more abstract representations remains unclear. Using a temporal pattern discrimination task in trained monkeys, we revealed that the second somatosensory cortex (S2) efficiently segregates faithful and transformed neural responses into orthogonal subspaces. Importantly, S2 population encoding for transformed signals, but not for faithful ones, disappeared during a nondemanding version of this task, which suggests that signal transformation and their decoding from downstream areas are only active on-demand. A mechanistic computation model points to gain modulation as a possible biological mechanism for the observed context-dependent computation. Furthermore, individual neural activities that underlie the orthogonal population representations exhibited a continuum of responses, with no well-determined clusters. These findings advocate that the brain, while employing a continuum of heterogeneous neural responses, splits population signals into orthogonal subspaces in a context-dependent fashion to enhance robustness, performance, and improve coding efficiency.

Hierarchical unimodal processing within the primary somatosensory cortex during a bimodal detection task.

Do sensory cortices process more than one sensory modality? To answer these questions, scientists have generated a wide variety of studies at distinct space-time scales in different animal models, and often shown contradictory conclusions. Some conclude that this process occurs in early sensory cortices, but others that this occurs in areas central to sensory cortices. Here, we sought to determine whether sensory neurons process and encode physical stimulus properties of different modalities (tactile and acoustic). For this, we designed a bimodal detection task where the senses of touch and hearing compete from trial to trial. Two Rhesus monkeys performed this novel task, while neural activity was recorded in areas 3b and 1 of the primary somatosensory cortex (S1). We analyzed neurons' coding properties and variability, organizing them by their receptive field's position relative to the stimulation zone. Our results indicate that neurons of areas 3b and 1 are unimodal, encoding only the tactile modality in both the firing rate and variability. Moreover, we found that neurons in area 3b carried more information about the periodic stimulus structure than those in area 1, possessed lower response and coding latencies, and had a lower intrinsic time scale. In sum, these differences reveal a hidden processing-based hierarchy. Finally, using a powerful nonlinear dimensionality reduction algorithm, we show that the activity from areas 3b and 1 can be separated, establishing a clear division in the functionality of these two subareas of S1.

An abstract categorical decision code in dorsal premotor cortex.

The dorsal premotor cortex (DPC) has classically been associated with a role in preparing and executing the physical motor variables during cognitive tasks. While recent work has provided nuanced insights into this role, here we propose that DPC also participates more actively in decision-making. We recorded neuronal activity in DPC while two trained monkeys performed a vibrotactile categorization task, utilizing two partially overlapping ranges of stimulus values that varied on two physical attributes: vibrotactile frequency and amplitude. We observed a broad heterogeneity across DPC neurons, the majority of which maintained the same response patterns across attributes and ranges, coding in the same periods, mixing temporal and categorical dynamics. The predominant categorical signal was maintained throughout the delay, movement periods and notably during the intertrial period. Putting the entire population's data through two dimensionality reduction techniques, we found strong temporal and categorical representations without remnants of the stimuli's physical parameters. Furthermore, projecting the activity of one population over the population axes of the other yielded identical categorical and temporal responses. Finally, we sought to identify functional subpopulations based on the combined activity of all stimuli, neurons, and time points; however, we found that single-unit responses mixed temporal and categorical dynamics and couldn't be clustered. All these point to DPC playing a more decision-related role than previously anticipated.

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.

Temporal signals underlying a cognitive process in the dorsal premotor cortex.

During discrimination between two sequential vibrotactile stimulus patterns, the primate dorsal premotor cortex (DPC) neurons exhibit a complex repertoire of coding dynamics associated with the working memory, comparison, and decision components of this task. In addition, these neurons and neurons with no coding responses show complex strong fluctuations in their firing rate associated with the temporal sequence of task events. Here, to make sense of this temporal complexity, we extracted the temporal signals that were latent in the population. We found a strong link between the individual and population response, suggesting a common neural substrate. Notably, in contrast to coding dynamics, these time-dependent responses were unaffected during error trials. However, in a nondemanding task in which monkeys did not require discrimination for reward, these time-dependent signals were largely reduced and changed. These results suggest that temporal dynamics in DPC reflect the underlying cognitive processes of this task.

Feed-forward information and zero-lag synchronization in the sensory thalamocortical circuit are modulated during stimulus perception.

The direction of functional information flow in the sensory thalamocortical circuit may play a role in stimulus perception, but, surprisingly, this process is poorly understood. We addressed this problem by evaluating a directional information measure between simultaneously recorded neurons from somatosensory thalamus (ventral posterolateral nucleus, VPL) and somatosensory cortex (S1) sharing the same cutaneous receptive field while monkeys judged the presence or absence of a tactile stimulus. During stimulus presence, feed-forward information (VPL → S1) increased as a function of the stimulus amplitude, while pure feed-back information (S1 → VPL) was unaffected. In parallel, zero-lag interaction emerged with increasing stimulus amplitude, reflecting externally driven thalamocortical synchronization during stimulus processing. Furthermore, VPL → S1 information decreased during error trials. Also, VPL → S1 and zero-lag interaction decreased when monkeys were not required to report the stimulus presence. These findings provide evidence that both the direction of information flow and the instant synchronization in the sensory thalamocortical circuit play a role in stimulus perception.

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.

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.

Local domains of motor cortical activity revealed by fiber-optic calcium recordings in behaving nonhuman primates.

Brain mapping experiments involving electrical microstimulation indicate that the primary motor cortex (M1) directly regulates muscle contraction and thereby controls specific movements. Possibly, M1 contains a small circuit "map" of the body that is formed by discrete local networks that code for specific movements. Alternatively, movements may be controlled by distributed, larger-scale overlapping circuits. Because of technical limitations, it remained unclear how movement-determining circuits are organized in M1. Here we introduce a method that allows the functional mapping of small local neuronal circuits in awake behaving nonhuman primates. For this purpose, we combined optic-fiber-based calcium recordings of neuronal activity and cortical microstimulation. The method requires targeted bulk loading of synthetic calcium indicators (e.g., OGB-1 AM) for the staining of neuronal microdomains. The tip of a thin (200 µm) optical fiber can detect the coherent activity of a small cluster of neurons, but is insensitive to the asynchronous activity of individual cells. By combining such optical recordings with microstimulation at two well-separated sites of M1, we demonstrate that local cortical activity was tightly associated with distinct and stereotypical simple movements. Increasing stimulation intensity increased both the amplitude of the movements and the level of neuronal activity. Importantly, the activity remained local, without invading the recording domain of the second optical fiber. Furthermore, there was clear response specificity at the two recording sites in a trained behavioral task. Thus, the results provide support for movement control in M1 by local neuronal clusters that are organized in discrete cortical domains.

Thalamocortical rhythms during a vibrotactile detection task.

To explore the role of oscillatory dynamics of the somatosensory thalamocortical network in perception and decision making, we recorded the simultaneous neuronal activity in the ventral posterolateral nucleus (VPL) of the somatosensory thalamus and primary somatosensory cortex (S1) in two macaque monkeys performing a vibrotactile detection task. Actively detecting a vibrotactile stimulus and reporting its perception elicited a sustained poststimulus beta power increase in VPL and an alpha power decrease in S1, in both stimulus-present and stimulus-absent trials. These oscillatory dynamics in the somatosensory thalamocortical network depended on the behavioral context: they were stronger for the active detection condition than for a passive stimulation condition. Furthermore, contrasting stimulus-present vs. stimulus-absent responses, we found that poststimulus theta power increased in both VPL and S1, and alpha/beta power decreased in S1, reflecting the monkey's perceptual decision but not the motor response per se. Additionally, higher prestimulus alpha power in S1 correlated with an increased probability of the monkey reporting a stimulus, regardless of the actual presence of a stimulus. Thus, we found task-related modulations in oscillatory activity, not only in the neocortex but also in the thalamus, depending on behavioral context. Furthermore, oscillatory modulations reflected the perceptual decision process and subsequent behavioral response. We conclude that these early sensory regions, in addition to their primary sensory functions, may be actively involved in perceptual decision making.

Neural coding and perceptual detection in the primate somatosensory thalamus.

The contribution of the sensory thalamus to perception and decision making is not well understood. We addressed this problem by recording single neurons in the ventral posterior lateral (VPL) nucleus of the somatosensory thalamus while trained monkeys judged the presence or absence of a vibrotactile stimulus of variable amplitude applied to the skin of a fingertip. We found that neurons in the VPL nucleus modulated their firing rate as a function of stimulus amplitude, and that such modulations accounted for the monkeys' overall psychophysical performance. These neural responses did not predict the animals' decision reports in individual trials, however. Moreover, the sensitivity to changes in stimulus amplitude was similar when the monkeys' performed the detection task and when they were not required to report stimulus detection. These results suggest that the primate somatosensory thalamus likely provides a reliable neural representation of the sensory input to the cerebral cortex, where sensory information is transformed and combined with other cognitive components associated with behavioral performance.

Thalamocortical interactions shape hierarchical neural variability during stimulus perception.

The brain is organized hierarchically to process sensory signals. But, how do functional connections within and across areas contribute to this hierarchical order? We addressed this problem in the thalamocortical network, while monkeys detected vibrotactile stimulus. During this task, we quantified neural variability and directed functional connectivity in simultaneously recorded neurons sharing the cutaneous receptive field within and across VPL and areas 3b and 1. Before stimulus onset, VPL and area 3b exhibited similar fast dynamics while area 1 showed slower timescales. During the stimulus presence, inter-trial neural variability increased along the network VPL-3b-1 while VPL established two main feedforward pathways with areas 3b and 1 to process the stimulus. This lower variability of VPL and area 3b was found to regulate feedforward thalamocortical pathways. Instead, intra-cortical interactions were only anticipated by higher intrinsic timescales in area 1. Overall, our results provide evidence of hierarchical functional roles along the thalamocortical network.

Heterogenous population coding of a short-term memory and decision task.

We examined neural spike recordings from prefrontal cortex (PFC) while monkeys performed a delayed somatosensory discrimination task. In general, PFC neurons displayed great heterogeneity in response to the task. That is, although individual cells spiked reliably in response to task variables from trial-to-trial, each cell had idiosyncratic combinations of response properties. Despite the great variety in response types, some general patterns held. We used linear regression analysis on the spike data to both display the full heterogeneity of the data and classify cells into categories. We compared different categories of cells and found little difference in their ability to carry information about task variables or their correlation to behavior. This suggests a distributed neural code for the task rather than a highly modularized one. Along this line, we compared the predictions of two theoretical models to the data. We found that cell types predicted by both models were not represented significantly in the population. Our study points to a different class of models that should embrace the inherent heterogeneity of the data, but should also account for the nonrandom features of the population.

Procedure for recording the simultaneous activity of single neurons distributed across cortical areas during sensory discrimination.

We report a procedure for recording the simultaneous activity of single neurons distributed across five cortical areas in behaving monkeys. The procedure consists of a commercially available microdrive adapted to a commercially available neural data collection system. The critical advantage of this procedure is that, in each cortical area, a configuration of seven microelectrodes spaced 250-500 mum can be inserted transdurally and each can be moved independently in the z axis. For each microelectrode, the data collection system can record the activity of up to five neurons together with the local field potential (LFP). With this procedure, we normally monitor the simultaneous activity of 70-100 neurons while trained monkeys discriminate the difference in frequency between two vibrotactile stimuli. Approximately 20-60 of these neurons have response properties previously reported in this task. The neuronal recordings show good signal-to-noise ratio, are remarkably stable along a 1-day session, and allow testing several protocols. Microelectrodes are removed from the brain after a 1-day recording session, but are reinserted again the next day by using the same or different x-y microelectrode array configurations. The fact that microelectrodes can be moved in the z axis during the recording session and that the x-y configuration can be changed from day to day maximizes the probability of studying simultaneous interactions, both local and across distant cortical areas, between neurons associated with the different components of this task.

A continuum of invariant sensory and behavioral-context perceptual coding in secondary somatosensory cortex.

A crucial role of cortical networks is the conversion of sensory inputs into perception. In the cortical somatosensory network, neurons of the primary somatosensory cortex (S1) show invariant sensory responses, while frontal lobe neuronal activity correlates with the animal's perceptual behavior. Here, we report that in the secondary somatosensory cortex (S2), neurons with invariant sensory responses coexist with neurons whose responses correlate with perceptual behavior. Importantly, the vast majority of the neurons fall along a continuum of combined sensory and categorical dynamics. Furthermore, during a non-demanding control task, the sensory responses remain unaltered while the sensory information exhibits an increase. However, perceptual responses and the associated categorical information decrease, implicating a task context-dependent processing mechanism. Conclusively, S2 neurons exhibit intriguing dynamics that are intermediate between those of S1 and frontal lobe. Our results contribute relevant evidence about the role that S2 plays in the conversion of touch into perception.

Neuronal correlates of a perceptual decision in ventral premotor cortex.

The ventral premotor cortex (VPC) is involved in the transformation of sensory information into action, although the exact neuronal operation is not known. We addressed this problem by recording from single neurons in VPC while trained monkeys report a decision based on the comparison of two mechanical vibrations applied sequentially to the fingertips. Here we report that the activity of VPC neurons reflects current and remembered sensory inputs, their comparison, and motor commands expressing the result; that is, the entire processing cascade linking the evaluation of sensory stimuli with a motor report. These findings provide a fairly complete panorama of the neural dynamics that underlies the transformation of sensory information into an action and emphasize the role of VPC in perceptual decisions.

Temporal evolution of a decision-making process in medial premotor cortex.

The events linking sensory discrimination to motor action remain unclear. It is not known, for example, whether the motor areas of the frontal lobe receive the result of the discrimination process from other areas or whether they actively participate in it. To investigate this, we trained monkeys to discriminate between two mechanical vibrations applied sequentially to the fingertips; here subjects had to recall the first vibration, compare it to the second one, and indicate with a hand/arm movement which of the two vibrations had the higher frequency. We recorded the activity of single neurons in medial premotor cortex (MPC) and found that their responses correlate with the diverse stages of the discrimination process. Thus, activity in MPC reflects the temporal evolution of the decision-making process leading to action selection during this perceptual task.

Correlated neuronal discharges that increase coding efficiency during perceptual discrimination.

During a sensory discrimination task, the responses of multiple sensory neurons must be combined to generate a choice. The optimal combination of responses is determined both by their dependence on the sensory stimulus and by their cofluctuations across trials-that is, the noise correlations. Positively correlated noise is considered deleterious, because it limits the coding accuracy of populations of similarly tuned neurons. However, positively correlated fluctuations between differently tuned neurons actually increase coding accuracy, because they allow the common noise to be subtracted without signal loss. This is demonstrated with data recorded from the secondary somatosensory cortex of monkeys performing a vibrotactile discrimination task. The results indicate that positive correlations are not always harmful and may be exploited by cortical networks to enhance the neural representation of features to be discriminated.

Neuronal correlates of decision-making in secondary somatosensory cortex.

The ability to discriminate between two sequential stimuli requires evaluation of current sensory information in reference to stored information. Where and how does this evaluation occur? We trained monkeys to compare two mechanical vibrations applied sequentially to the fingertips and to report which of the two had the higher frequency. We recorded single neurons in secondary somatosensory cortex (S2) while the monkeys performed the task. During the first stimulus period, the firing rate of S2 neurons encoded the stimulus frequency. During the second stimulus period, however, some S2 neurons did not merely encode the stimulus frequency. The responses of these neurons were a function of both the remembered (first) and current (second) stimulus. Moreover, a few hundred milliseconds after the presentation of the second stimulus, these responses were correlated with the monkey's decision. This suggests that some S2 neurons may combine past and present sensory information for decision-making.

Decoding a Decision Process in the Neuronal Population of Dorsal Premotor Cortex.

When trained monkeys discriminate the temporal structure of two sequential vibrotactile stimuli, dorsal premotor cortex (DPC) showed high heterogeneity among its neuronal responses. Notably, DPC neurons coded stimulus patterns as broader categories and signaled them during working memory, comparison, and postponed decision periods. Here, we show that such population activity can be condensed into two major coding components: one that persistently represented in working memory both the first stimulus identity and the postponed informed choice and another that transiently coded the initial sensory information and the result of the comparison between the two stimuli. Additionally, we identified relevant signals that coded the timing of task events. These temporal and task-parameter readouts were shown to be strongly linked to the monkeys' behavior when contrasted to those obtained in a non-demanding cognitive control task and during error trials. These signals, hidden in the heterogeneity, were prominently represented by the DPC population response.