Functional properties of primate putamen neurons during the categorization of tactile stimuli

Distinct neural adaptations to time demand in the striatum and the hippocampus

How do neural codes adjust to track time across a range of resolutions, from milliseconds to multi-seconds, as a function of the temporal frequency at which events occur? To address this question, we studied time-modulated cells in the striatum and the hippocampus, while macaques categorized three nested intervals within the sub-second or the supra-second range (up to 1, 2, 4, or 8 s), thereby modifying the temporal resolution needed to solve the task. Time-modulated cells carried more information for intervals with explicit timing demand, than for any other interval. The striatum, particularly the caudate, supported the most accurate temporal prediction throughout all time ranges. Strikingly, its temporal readout adjusted non-linearly to the time range, suggesting that the striatal resolution shifted from a precise millisecond to a coarse multi-second range as a function of demand. This is in line with monkey's behavioral latencies, which indicated that they tracked time until 2 s but employed a coarse categorization strategy for durations beyond. By contrast, the hippocampus discriminated only the beginning from the end of intervals, regardless of the range. We propose that the hippocampus may provide an overall poor signal marking an event's beginning, whereas the striatum optimizes neural resources to process time throughout an interval adapting to the ongoing timing necessity.

Contributions of the Basal Ganglia to Visual Perceptual Decisions

The basal ganglia (BG) make up a prominent nexus between visual and motor-related brain regions. In contrast to the BG's well-established roles in movement control and value-based decision making, their contributions to the transformation of visual input into an action remain unclear, especially in the context of perceptual decisions based on uncertain visual evidence. This article reviews recent progress in our understanding of the BG's contributions to the formation, evaluation, and adjustment of such decisions. From theoretical and experimental perspectives, the review focuses on four key stations in the BG network, namely, the striatum, pallidum, subthalamic nucleus, and midbrain dopamine neurons, which can have different roles and together support the decision process.

Sensory representations in the striatum provide a temporal reference for learning and executing motor habits

Previous studies indicate that the dorsolateral striatum (DLS) integrates sensorimotor information from cortical and thalamic regions to learn and execute motor habits. However, the exact contribution of sensory representations to this process is still unknown. Here we explore the role of the forelimb somatosensory flow in the DLS during the learning and execution of motor habits. First, we compare rhythmic somesthetic representations in the DLS and primary somatosensory cortex in anesthetized rats, and find that sequential and temporal stimuli contents are more strongly represented in the DLS. Then, using a behavioral protocol in which rats developed a stereotyped motor sequence, functional disconnection experiments, and pharmacologic and optogenetic manipulations in apprentice and expert animals, we reveal that somatosensory thalamic- and cortical-striatal pathways are indispensable for the temporal component of execution. Our results indicate that the somatosensory flow in the DLS provides the temporal reference for the development and execution of motor habits.

The authors combine anatomical mapping, electrophysiological recordings, lesions, and pharmacological and optogenetic manipulations in rats to examine the role of forelimb somatosensory flow in the dorsolateral striatum in the learning and execution of motor habits.

Brain networks underlying tactile softness perception: A functional magnetic resonance imaging study

Humans are adept at perceiving physical properties of an object through touch. Tangible object properties can be categorized into two types: macro-spatial properties, including shape and orientation; and material properties, such as roughness, softness, and temperature. Previous neuroimaging studies have shown that roughness and temperature are extracted at nodes of a network, such as that involving the parietal operculum and insula, which is different from the network engaged in processing macro-spatial properties. However, it is unclear whether other perceptual dimensions pertaining to material properties engage the same regions. Here, we conducted a functional magnetic resonance imaging study to test whether the parietal operculum and insula were involved in extracting tactually-perceived softness magnitude. Fifty-six healthy right-handed participants estimated perceived softness magnitude using their right middle finger. We presented three stimuli that had the same shape but different compliances. The force applied to the finger was manipulated at two levels. Classical mass-univariate analysis showed that activity in the parietal operculum, insula, and medial prefrontal cortex was positively associated with perceived softness magnitude, regardless of the applied force. Softness-related activity was stronger in the ventral striatum in the high-force condition than in the low-force condition. The multivariate voxel pattern analysis showed higher accuracy than chance levels and control regions in the parietal operculum/insula, postcentral gyrus, posterior parietal lobule, and middle occipital gyrus. These results indicate that a distributed set of the brain regions, including the parietal operculum and insula, is involved in representing perceived softness.

The scalar property during isochronous tapping is disrupted by a D2-like agonist in the nonhuman primate

Dopamine, and specifically the D2 system, has been implicated in timing tasks where the absolute duration of individual time intervals is encoded discretely, yet the role of D2 during beat perception and entrainment remains largely unknown. In this type of timing, a beat is perceived as the pulse that marks equally spaced points in time and, once extracted, produces the tendency in humans to entrain or synchronize their movements to it. Hence, beat-based timing is crucial for musical execution. In this study we investigated the effects of systemic injections of quinpirole (0.005–0.05 mg/kg), a D2-like agonist, on the isochronous rhythmic tapping of rhesus monkeys, a classical task for the study of beat entrainment. We compared the rhythmic timing accuracy, precision, and the asynchronies of the monkeys with or without the effects of quinpirole, as well as their reaction times in a control serial reaction time task (SRTT). The results showed a dose-dependent disruption in the scalar property of rhythmic timing due to quinpirole administration. Specifically, we found similar temporal variabilities as a function of the metronome tempo at the largest dose, instead of the increase in variability across durations that is characteristic of the timing Weber law. Notably, these effects were not due to alterations in the basic sensorimotor mechanism for tapping to a sequence of flashing stimuli, because quinpirole did not change the reaction time of the monkeys during SRTT. These findings support the notion of a key role of the D2 system in the rhythmic timing mechanism, especially in the control of temporal precision.

NEW & NOTEWORTHY Perceiving and moving to the beat of music is a fundamental trait of musical cognition. We measured the effect of quinpirole, a D2-like agonist, on the precision and accuracy of rhythmic tapping to a metronome in two rhesus monkeys. Quinpirole produced a flattening of the temporal variability as a function of tempo duration, instead of the increase in variability across durations that is characteristic of the scalar property, a hallmark property of timing.

The Thalamostriatal Projections Contribute to the Initiation and Execution of a Sequence of Movements

One of the main inputs driving striatal activity is the thalamostriatal projection. While the hypothesis postulating that the different thalamostriatal projections contribute differentially to shape the functions of the striatum is largely accepted, existing technical limitations have hampered efforts to prove it. Here, through the use of electrophysiological recordings of antidromically photo-identified thalamostriatal neurons and the optogenetic inhibition of thalamostriatal terminals, we identify that the thalamostriatal projections from the parafascicular and the ventroposterior regions of the thalamus contribute to the smooth initiation and the appropriate execution of a sequence of movements. Our results support a model in which both thalamostriatal projections have specific contributions to the initiation and execution of sequences, highlighting the specific contribution of the ventroposterior thalamostriatal connection for the repetition of actions.

On the Role of Cortex-Basal Ganglia Interactions for Category Learning: A Neurocomputational Approach

In addition to the prefrontal cortex (PFC), the basal ganglia (BG) have been increasingly often reported to play a fundamental role in category learning, but the circuit mechanisms mediating their interaction remain to be explored. We developed a novel neurocomputational model of category learning that particularly addresses the BG-PFC interplay. We propose that the BG bias PFC activity by removing the inhibition of cortico-thalamo-cortical loop and thereby provide a teaching signal to guide the acquisition of category representations in the corticocortical associations to the PFC. Our model replicates key behavioral and physiological data of macaque monkey learning a prototype distortion task from Antzoulatos and Miller (2011) Our simulations allowed us to gain a deeper insight into the observed drop of category selectivity in striatal neurons seen in the experimental data and in the model. The simulation results and a new analysis of the experimental data based on the model's predictions show that the drop in category selectivity of the striatum emerges as the variability of responses in the striatum rises when confronting the BG with an increasingly larger number of stimuli to be classified. The neurocomputational model therefore provides new testable insights of systems-level brain circuits involved in category learning that may also be generalized to better understand other cortico-BG-cortical loops.SIGNIFICANCE STATEMENT Inspired by the idea that basal ganglia (BG) teach the prefrontal cortex (PFC) to acquire category representations, we developed a novel neurocomputational model and tested it on a task that was recently applied in monkey experiments. As an advantage over previous models of category learning, our model allows to compare simulation data with single-cell recordings in PFC and BG. We not only derived model predictions, but already verified a prediction to explain the observed drop in striatal category selectivity. When testing our model with a simple, real-world face categorization task, we observed that the fast striatal learning with a performance of 85% correct responses can teach the slower PFC learning to push the model performance up to almost 100%.

Cognitive changes in conjunctive rule-based category learning: An ERP approach

When learning rule-based categories, sufficient cognitive resources are needed to test hypotheses, maintain the currently active rule in working memory, update rules after feedback, and to select a new rule if necessary. Prior research has demonstrated that conjunctive rules are more complex than unidimensional rules and place greater demands on executive functions like working memory. In our study, event-related potentials (ERPs) were recorded while participants performed a conjunctive rule-based category learning task with trial-by-trial feedback. In line with prior research, correct categorization responses resulted in a larger stimulus-locked late positive complex compared to incorrect responses, possibly indexing the updating of rule information in memory. Incorrect trials elicited a pronounced feedback-locked P300 elicited which suggested a disconnect between perception, and the rule-based strategy. We also examined the differential processing of stimuli that were able to be correctly classified by the suboptimal single-dimensional rule ("easy" stimuli) versus those that could only be correctly classified by the optimal, conjunctive rule ("difficult" stimuli). Among strong learners, a larger, late positive slow wave emerged for difficult compared with easy stimuli, suggesting differential processing of category items even though strong learners performed well on the conjunctive category set. Overall, the findings suggest that ERP combined with computational modelling can be used to better understand the cognitive processes involved in rule-based category learning.

Neural basis for categorical boundaries in the primate pre-SMA during relative categorization of time intervals

Perceptual categorization depends on the assignment of different stimuli to specific groups based, in principle, on the notion of flexible categorical boundaries. To determine the neural basis of categorical boundaries, we record the activity of pre-SMA neurons of monkeys executing an interval categorization task in which the limit between short and long categories changes between blocks of trials within a session. A large population of cells encodes this boundary by reaching a constant peak of activity close to the corresponding subjective limit. Notably, the time at which this peak is reached changes according to the categorical boundary of the current block, predicting the monkeys’ categorical decision on a trial-by-trial basis. In addition, pre-SMA cells also represent the category selected by the monkeys and the outcome of the decision. These results suggest that the pre-SMA adaptively encodes subjective duration boundaries between short and long durations and contains crucial neural information to categorize intervals and evaluate the outcome of such perceptual decisions.

Grouping stimuli into categories often depends on a subjective determination of category boundaries. Here the authors report a neuronal population in pre-supplementary motor area whose peak activity predicts the categorical decision boundary between long and short time intervals on a trial-by-trial basis.

Different Levels of Category Abstraction by Different Dynamics in Different Prefrontal Areas

Categories can be grouped by shared sensory attributes (i.e., cats) or a more abstract rule (i.e., animals). We explored the neural basis of abstraction by recording from multi-electrode arrays in prefrontal cortex (PFC) while monkeys performed a dot-pattern categorization task. Category abstraction was varied by the degree of exemplar distortion from the prototype pattern. Different dynamics in different PFC regions processed different levels of category abstraction. Bottom-up dynamics (stimulus-locked gamma power and spiking) in the ventral PFC processed more low-level abstractions, whereas top-down dynamics (beta power and beta spike-LFP coherence) in the dorsal PFC processed more high-level abstractions. Our results suggest a two-stage, rhythm-based model for abstracting categories.

Response properties of neurons in the cat's putamen during auditory discrimination

The striatum integrates diverse convergent input and plays a critical role in the goal-directed behaviors. To date, the auditory functions of striatum are less studied. Recently, it was demonstrated that auditory cortico-striatal projections influence behavioral performance during a frequency discrimination task. To reveal the functions of striatal neurons in auditory discrimination, we recorded the single-unit spike activities in the putamen (dorsal striatum) of free-moving cats while performing a Go/No-go task to discriminate the sounds with different modulation rates (12.5 Hz vs. 50 Hz) or envelopes (damped vs. ramped). We found that the putamen neurons can be broadly divided into four groups according to their contributions to sound discrimination. First, 40% of neurons showed vigorous responses synchronized to the sound envelope, and could precisely discriminate different sounds. Second, 18% of neurons showed a high preference of ramped to damped sounds, but no preference for modulation rate. They could only discriminate the change of sound envelope. Third, 27% of neurons rapidly adapted to the sound stimuli, had no ability of sound discrimination. Fourth, 15% of neurons discriminated the sounds dependent on the reward-prediction. Comparing to passively listening condition, the activities of putamen neurons were significantly enhanced by the engagement of the auditory tasks, but not modulated by the cat's behavioral choice. The coexistence of multiple types of neurons suggests that the putamen is involved in the transformation from auditory representation to stimulus-reward association.

Differential effects of dopamine-directed treatments on cognition

Dopamine, a prominent neuromodulator, is implicated in many neuropsychiatric disorders. It has wide-ranging effects on both cortical and subcortical brain regions and on many types of cognitive tasks that rely on a variety of different learning and memory systems. As neuroscience and behavioral evidence for the existence of multiple memory systems and their corresponding neural networks accumulated, so did the notion that dopamine's role is markedly different depending on which memory system is engaged. As a result, dopamine-directed treatments will have different effects on different types of cognitive behaviors. To predict what these effects will be, it is critical to understand: which memory system is mediating the behavior; the neural basis of the mediating memory system; the nature of the dopamine projections into that system; and the time course of dopamine after its release into the relevant brain regions. Consideration of these questions leads to different predictions for how changes in brain dopamine levels will affect automatic behaviors and behaviors mediated by declarative, procedural, and perceptual representation memory systems.

Finding the beat: a neural perspective across humans and non-human primates

Humans possess an ability to perceive and synchronize movements to the beat in music ('beat perception and synchronization'), and recent neuroscientific data have offered new insights into this beat-finding capacity at multiple neural levels. Here, we review and compare behavioural and neural data on temporal and sequential processing during beat perception and entrainment tasks in macaques (including direct neural recording and local field potential (LFP)) and humans (including fMRI, EEG and MEG). These abilities rest upon a distributed set of circuits that include the motor cortico-basal-ganglia-thalamo-cortical (mCBGT) circuit, where the supplementary motor cortex (SMA) and the putamen are critical cortical and subcortical nodes, respectively. In addition, a cortical loop between motor and auditory areas, connected through delta and beta oscillatory activity, is deeply involved in these behaviours, with motor regions providing the predictive timing needed for the perception of, and entrainment to, musical rhythms. The neural discharge rate and the LFP oscillatory activity in the gamma- and beta-bands in the putamen and SMA of monkeys are tuned to the duration of intervals produced during a beat synchronization-continuation task (SCT). Hence, the tempo during beat synchronization is represented by different interval-tuned cells that are activated depending on the produced interval. In addition, cells in these areas are tuned to the serial-order elements of the SCT. Thus, the underpinnings of beat synchronization are intrinsically linked to the dynamics of cell populations tuned for duration and serial order throughout the mCBGT. We suggest that a cross-species comparison of behaviours and the neural circuits supporting them sets the stage for a new generation of neurally grounded computational models for beat perception and synchronization.

Motor system evolution and the emergence of high cognitive functions

In human and nonhuman primates, the cortical motor system comprises a collection of brain areas primarily related to motor control. Existing evidence suggests that no other mammalian group has the number, extension, and complexity of motor-related areas observed in the frontal lobe of primates. Such diversity is probably related to the wide behavioral flexibility that primates display. Indeed, recent comparative anatomical, psychophysical, and neurophysiological studies suggest that the evolution of the motor cortical areas closely correlates with the emergence of high cognitive abilities. Advances in understanding the cortical motor system have shown that these areas are also related to functions previously linked to higher-order associative areas. In addition, experimental observations have shown that the classical distinction between perceptual and motor functions is not strictly followed across cortical areas. In this paper, we review evidence suggesting that evolution of the motor system had a role in the shaping of different cognitive functions in primates. We argue that the increase in the complexity of the motor system has contributed to the emergence of new abilities observed in human and nonhuman primates, including the recognition and imitation of the actions of others, speech perception and production, and the execution and appreciation of the rhythmic structure of music.

Cognitive modulation of local and callosal neural interactions in decision making

Traditionally, the neurophysiological mechanisms of cognitive processing have been investigated at the single cell level. Here we show that the dynamic, millisecond-by-millisecond, interactions between neuronal events measured by local field potentials are modulated in an orderly fashion by key task variables of a space categorization task performed by monkeys. These interactions were stronger during periods of higher cognitive load and varied in sign (positive, negative). They were observed both within area 7a of the posterior parietal cortex and between symmetric 7a areas of the two hemispheres. Time lags for maximum interactions were longer for opposite- vs. same-hemisphere recordings, and lags for negative interactions were longer than for positive interactions in both recording sites. These findings underscore the involvement of dynamic neuronal interactions in cognitive processing within and across hemispheres. They also provide accurate estimates of lags in callosal interactions, very comparable to similar estimates of callosal conduction delays derived from neuroanatomical measurements (Caminiti et al., 2013).

Linking perception, cognition, and action: psychophysical observations and neural network modelling

It has been argued that perception, decision making, and movement planning are in reality tightly interwoven brain processes. However, how they are implemented in neural circuits is still a matter of debate. We tested human subjects in a temporal categorization task in which intervals had to be categorized as short or long. Subjects communicated their decision by moving a cursor into one of two possible targets, which appeared separated by different angles from trial to trial. Even though there was a 1 second-long delay between interval presentation and decision communication, categorization difficulty affected subjects’ performance, reaction (RT) and movement time (MT). In addition, reaction and movement times were also influenced by the distance between the targets. This implies that not only perceptual, but also movement-related considerations were incorporated into the decision process. Therefore, we searched for a model that could use categorization difficulty and target separation to describe subjects’ performance, RT, and MT. We developed a network consisting of two mutually inhibiting neural populations, each tuned to one of the possible categories and composed of an accumulation and a memory node. This network sequentially acquired interval information, maintained it in working memory and was then attracted to one of two possible states, corresponding to a categorical decision. It faithfully replicated subjects’ RT and MT as a function of categorization difficulty and target distance; it also replicated performance as a function of categorization difficulty. Furthermore, this model was used to make new predictions about the effect of untested durations, target distances and delay durations. To our knowledge, this is the first biologically plausible model that has been proposed to account for decision making and communication by integrating both sensory and motor planning information.

Information processing in the primate basal ganglia during sensory-guided and internally driven rhythmic tapping

Gamma (γ) and beta (β) oscillations seem to play complementary functions in the cortico-basal ganglia-thalamo-cortical circuit (CBGT) during motor behavior. We investigated the time-varying changes of the putaminal spiking activity and the spectral power of local field potentials (LFPs) during a task where the rhythmic tapping of monkeys was guided by isochronous stimuli separated by a fixed duration (synchronization phase), followed by a period of internally timed movements (continuation phase). We found that the power of both bands and the discharge rate of cells showed an orderly change in magnitude as a function of the duration and/or the serial order of the intervals executed rhythmically. More LFPs were tuned to duration and/or serial order in the β- than the γ-band, although different values of preferred features were represented by single cells and by both bands. Importantly, in the LFPs tuned to serial order, there was a strong bias toward the continuation phase for the β-band when aligned to movements, and a bias toward the synchronization phase for the γ-band when aligned to the stimuli. Our results suggest that γ-oscillations reflect local computations associated with stimulus processing, whereas β-activity involves the entrainment of large putaminal circuits, probably in conjunction with other elements of CBGT, during internally driven rhythmic tapping.

Neural changes with tactile learning reflect decision-level reweighting of perceptual readout

Despite considerable work, the neural basis of perceptual learning remains uncertain. For visual learning, although some studies suggested that changes in early sensory representations are responsible, other studies point to decision-level reweighting of perceptual readout. These competing possibilities have not been examined in other sensory systems, investigating which could help resolve the issue. Here we report a study of human tactile microspatial learning in which participants achieved >six-fold decline in acuity threshold after multiple training sessions. Functional magnetic resonance imaging was performed during performance of the tactile microspatial task and a control, tactile temporal task. Effective connectivity between relevant brain regions was estimated using multivariate, autoregressive models of hidden neuronal variables obtained by deconvolution of the hemodynamic response. Training-specific increases in task-selective activation assessed using the task × session interaction and associated changes in effective connectivity primarily involved subcortical and anterior neocortical regions implicated in motor and/or decision processes, rather than somatosensory cortical regions. A control group of participants tested twice, without intervening training, exhibited neither threshold improvement nor increases in task-selective activation. Our observations argue that neuroplasticity mediating perceptual learning occurs at the stage of perceptual readout by decision networks. This is consonant with the growing shift away from strictly modular conceptualization of the brain toward the idea that complex network interactions underlie even simple tasks. The convergence of our findings on tactile learning with recent studies of visual learning reconciles earlier discrepancies in the literature on perceptual learning.

Conversion of sensory signals into perceptual decisions

A fundamental problem in neurobiology is to understand how brain circuits represent sensory information and how such representations give rise to perception, memory and decision-making. We demonstrate that a sensory stimulus engages multiple areas of the cerebral cortex, including primary sensory, prefrontal, premotor and motor cortices. As information transverses the cortical circuits it shows progressively more relation to perception, memory and decision reports. In particular, we show how somatosensory areas on the parietal lobe generate a parameterized representation of a tactile stimulus. This representation is maintained in working memory by prefrontal and premotor areas of the frontal lobe. The presentation of a second stimulus, that monkeys are trained to compare with the first, generates decision-related activity reflecting which stimulus had the higher frequency. Importantly, decision-related activity is observed across several cortical circuits including prefrontal, premotor and parietal cortices. Sensory information is encoded by neuronal populations with opposite tuning, and suggests that a simple subtraction operation could be the underlying mechanism by which past and present sensory information is compared to generate perceptual decisions.

Temporal and spatial categorization in human and non-human primates

It has been proposed that a functional overlap exists in the brain for temporal and spatial information processing. To test this, we designed two relative categorization tasks in which human subjects and a Rhesus monkey had to assign time intervals or distances to a "short" or "long" category according to varying prototypes. The performance of both species was analyzed using psychometric techniques that showed that they may have similar perceptual, memory, and/or decision mechanisms, specially for the estimation of time intervals. We also did a correlation analysis with human subjects' psychometric thresholds and the results imply that indeed, temporal and spatial information categorization share neural substrates. However, not all of the tested distances and intervals correlated with each other, suggesting the existence of sub-circuits that process restricted ranges of distances and intervals. A different analysis was done on the monkey data, in which the influence of the previous categorical prototypes was measured on the task currently being performed. Again, we found a significant interaction between previous and current interval and distance categorization. Overall, the present paper points toward common or at least partially overlapped neural circuits for temporal and spatial categorization in primates.

Differential activity patterns of putaminal neurons with inputs from the primary motor cortex and supplementary motor area in behaving monkeys

Activity patterns of projection neurons in the putamen were investigated in behaving monkeys. Stimulating electrodes were implanted chronically into the proximal (MIproximal) and distal (MIdistal) forelimb regions of the primary motor cortex (MI) and the forelimb region of the supplementary motor area (SMA). Cortical inputs to putaminal neurons were identified by excitatory orthodromic responses to stimulation of these motor cortices. Then, neuronal activity was recorded during the performance of a goal-directed reaching task with delay. Putaminal neurons with inputs from the MI and SMA showed different activity patterns, i.e., movement- and delay-related activity, during task performance. MI-recipient neurons increased activity in response to arm-reach movements, whereas SMA-recipient neurons increased activity during delay periods, as well as during movements. The activity pattern of MI + SMA-recipient neurons was of an intermediate type between those of MI- and SMA-recipient neurons. Approximately one-half of MIproximal-, SMA-, and MI + SMA-recipient neurons changed activities before the onset of movements, whereas a smaller number of MIdistal- and MIproximal + distal-recipient neurons did. Movement-related activity of MI-recipient neurons was modulated by target directions, whereas SMA- and MI + SMA-recipient neurons had a lower directional selectivity. MI-recipient neurons were located mainly in the ventrolateral part of the caudal aspect of the putamen, whereas SMA-recipient neurons were located in the dorsomedial part. MI + SMA-recipient neurons were found in between. The present results suggest that a subpopulation of putaminal neurons displays specific activity patterns depending on motor cortical inputs. Each subpopulation receives convergent or nonconvergent inputs from the MI and SMA, retains specific motor information, and sends it to the globus pallidus and the substantia nigra through the direct and indirect pathways of the basal ganglia.

Top-down spatial categorization signal from prefrontal to posterior parietal cortex in the primate

In the present study we characterized the strength and time course of category-selective responses in prefrontal cortex and area 7a of the posterior parietal cortex during a match-to-sample spatial categorization task. A monkey was trained to categorize whether the height of a horizontal sample bar, presented in rectangular frame at one of three vertical locations, was "high" or "low," depending on whether its position was above or below the frame's midline. After the display of this sample bar, and after a delay, choice bars were sequentially flashed in two locations: at the top and at the bottom of the frame ("choice" epoch). If the monkey timed its response to the display of the choice bar that matched the sample bar, he was rewarded. We found that cells in prefrontal cortex discriminated category early after the initial sample bar was shown, and continued to differentiate "up" from "down" trials throughout the delay and choice periods. In contrast, parietal cells did not differentiate category until the choice period. Therefore, our results support the notion of a top-down categorical signal that originates in prefrontal cortex and that is only represented in parietal cortex when it is necessary to express the categorical decision through a movement.

The Neurodynamics of Cognition: A Tutorial on Computational Cognitive Neuroscience

Computational Cognitive Neuroscience (CCN) is a new field that lies at the intersection of computational neuroscience, machine learning, and neural network theory (i.e., connectionism). The ideal CCN model should not make any assumptions that are known to contradict the current neuroscience literature and at the same time provide good accounts of behavior and at least some neuroscience data (e.g., single-neuron activity, fMRI data). Furthermore, once set, the architecture of the CCN network and the models of each individual unit should remain fixed throughout all applications. Because of the greater weight they place on biological accuracy, CCN models differ substantially from traditional neural network models in how each individual unit is modeled, how learning is modeled, and how behavior is generated from the network. A variety of CCN solutions to these three problems are described. A real example of this approach is described, and some advantages and limitations of the CCN approach are discussed.

Category learning in the brain

The ability to group items and events into functional categories is a fundamental characteristic of sophisticated thought. It is subserved by plasticity in many neural systems, including neocortical regions (sensory, prefrontal, parietal, and motor cortex), the medial temporal lobe, the basal ganglia, and midbrain dopaminergic systems. These systems interact during category learning. Corticostriatal loops may mediate recursive, bootstrapping interactions between fast reward-gated plasticity in the basal ganglia and slow reward-shaded plasticity in the cortex. This can provide a balance between acquisition of details of experiences and generalization across them. Interactions between the corticostriatal loops can integrate perceptual, response, and feedback-related aspects of the task and mediate the shift from novice to skilled performance. The basal ganglia and medial temporal lobe interact competitively or cooperatively, depending on the demands of the learning task.

A computational model of how cholinergic interneurons protect striatal-dependent learning

An essential component of skill acquisition is learning the environmental conditions in which that skill is relevant. This article proposes and tests a neurobiologically detailed theory of how such learning is mediated. The theory assumes that a key component of this learning is provided by the cholinergic interneurons in the striatum known as tonically active neurons (TANs). The TANs are assumed to exert a tonic inhibitory influence over cortical inputs to the striatum that prevents the execution of any striatal-dependent actions. The TANs learn to pause in rewarding environments, and this pause releases the striatal output neurons from this inhibitory effect, thereby facilitating the learning and expression of striatal-dependent behaviors. When rewards are no longer available, the TANs cease to pause, which protects striatal learning from decay. A computational version of this theory accounts for a variety of single-cell recording data and some classic behavioral phenomena, including fast reacquisition after extinction.

Subsecond timing in primates: comparison of interval production between human subjects and rhesus monkeys

This study describes the psychometric similarities and differences in motor timing performance between 20 human subjects and three rhesus monkeys during two timing production tasks. These tasks involved tapping on a push-button to produce the same set of intervals (range of 450 to 1,000 ms), but they differed in the number of intervals produced (single vs. multiple) and the modality of the stimuli (auditory vs. visual) used to define the time intervals. The data showed that for both primate species, variability increased as a function of the length of the produced target interval across tasks, a result in accordance with the scalar property. Interestingly, the temporal performance of rhesus monkeys was equivalent to that of human subjects during both the production of single intervals and the tapping synchronization to a metronome. Overall, however, human subjects were more accurate than monkeys and showed less timing variability. This was especially true during the self-pacing phase of the multiple interval production task, a behavior that may be related to complex temporal cognition, such as speech and music execution. In addition, the well-known human bias toward auditory as opposed to visual cues for the accurate execution of time intervals was not evident in rhesus monkeys. These findings validate the rhesus monkey as an appropriate model for the study of the neural basis of time production, but also suggest that the exquisite temporal abilities of humans, which peak in speech and music performance, are not all shared with macaques.

Category label and response location shifts in category learning

The category shift literature suggests that rule-based classification, an important form of explicit learning, is mediated by two separate learned associations: a stimulus-to-label association that associates stimuli and category labels, and a label-to-response association that associates category labels and responses. Three experiments investigate whether information–integration classification, an important form of implicit learning, is also mediated by two separate learned associations. Participants were trained on a rule-based or an information–integration categorization task and then the association between stimulus and category label, or between category label and response location was altered. For rule-based categories, and in line with previous research, breaking the association between stimulus and category label caused more interference than breaking the association between category label and response location. However, no differences in recovery rate emerged. For information–integration categories, breaking the association between stimulus and category label caused more interference and led to greater recovery than breaking the association between category label and response location. These results provide evidence that information–integration category learning is mediated by separate stimulus-to-label and label-to-response associations. Implications for the neurobiological basis of these two learned associations are discussed.

Response processes in information-integration category learning

Much recent evidence suggests that human category learning is mediated by multiple systems. Evidence suggests that at least one of these depends on procedural learning within the basal ganglia. Information-integration categorization tasks are thought to load heavily on this procedural-learning system. The results of several previous studies were interpreted to suggest that response positions are learned in information-integration tasks. This hypothesis was tested in two experiments. Experiment 1 showed that information-integration category learning was slowed but not disrupted when the spatial location of the responses varied randomly across trials. Experiment 2 showed that information-integration learning was impaired if category membership was signaled by responding to a Yes/No question and the category label had no consistent spatial location. These results suggest that information-integration category learning does not require consistent response locations. In these experiments, a consistent association between a category and a response feature was sufficient. The implication of these results for the neurobiology of information-integration category learning is discussed.

Functional integration across a gradient of corticostriatal channels controls UP state transitions in the dorsal striatum

Coordinated near-threshold depolarized states in cortical and striatal neurons may contribute to form functionally segregated channels of information processing. Recent anatomical studies have identified pathways that could support spiraling interactions across corticostriatal channels, but a functional outcome of such spiraling remains to be identified. Here, we examined whether plateau depolarizations (UP states) in striatal neurons relate better to active epochs in local field potentials recorded from closely related cortical areas than to those recorded in less-related cortical areas. Our results show that, in anesthetized rats, the coordination between cortical areas and striatal regions obeys a mediolateral gradient and keeps track of slow wave trajectory across the neocortex. Moreover, activity in one cortical area induced phase advances in UP state onset and phase delays in UP state termination in nonmatching striatal regions, reflecting the existence of functional connections that could encode large-scale interactions between corticostriatal channels as subthreshold influences on striatal projection neurons.

Linking cortical spike pattern codes to auditory perception

Abstract Neurometric analysis has proven to be a powerful tool for studying links between neural activity and perception, especially in visual and somatosensory cortices, but conventional neurometrics are based on a simplistic rate-coding hypothesis that is clearly at odds with the rich and complex temporal spiking patterns evoked by many natural stimuli. In this study, we investigated the possible relationships between temporal spike pattern codes in the primary auditory cortex (A1) and the perceptual detection of subtle changes in the temporal structure of a natural sound. Using a two-alternative forced-choice oddity task, we measured the ability of human listeners to detect local time reversals in a marmoset twitter call. We also recorded responses of neurons in A1 of anesthetized and awake ferrets to these stimuli, and analyzed these responses using a novel neurometric approach that is sensitive to temporal discharge patterns. We found that although spike count-based neurometrics were inadequate to account for behavioral performance on this auditory task, neurometrics based on the temporal discharge patterns of populations of A1 units closely matched the psychometric performance curve, but only if the spiking patterns were resolved at temporal resolutions of 20 msec or better. These results demonstrate that neurometric discrimination curves can be calculated for temporal spiking patterns, and they suggest that such an extension of previous spike count-based approaches is likely to be essential for understanding the neural correlates of the perception of stimuli with a complex temporal structure.

Neural correlates of a postponed decision report

Depending on environmental demands, a decision based on a sensory evaluation may be either immediately reported or postponed for later report. If postponed, the decision must be held in memory. But what exactly is stored by the underlying memory circuits, the final decision itself or the sensory information that led to it? Here, we report that, during a postponed decision report period, the activity of medial premotor cortex neurons encodes both the result of the sensory evaluation that corresponds to the monkey's possible choices and past sensory information on which the decision is based. These responses could switch back and forth with remarkable flexibility across the postponed decision report period. Moreover, these responses covaried with the animal's decision report. We propose that maintaining in working memory the original stimulus information on which the decision is based could serve to continuously update the postponed decision report in this task.

Focal putamen lesions impair learning in rule-based, but not information-integration categorization tasks

Previous research on the role of the basal ganglia in category learning has focused on patients with Parkinson's and Huntington's disease, neurodegenerative diseases frequently accompanied by additional cortical pathology. The goal of the present study was to extend this work to patients with basal ganglia lesions due to stroke, asking if similar changes in performance would be observed in patients with more focal pathology. Patients with basal ganglia lesions centered in the putamen (6 left side, 1 right side) were tested on rule-based and information-integration visual categorization tasks. In rule-based tasks, it is assumed that participants can learn the category structures through an explicit reasoning process. In information-integration tasks, optimal performance requires the integration of information from two or more stimulus components, and participants are typically unaware of the category rules. Consistent with previous studies involving patients with degenerative disorders of the basal ganglia, the stroke patients were impaired on the rule-based task, and quantitative, model-based analyses indicate that this deficit was due to the inefficient application of decision strategies. In contrast, the patients were unimpaired on the information-integration task. This pattern of results provides converging evidence supporting a role of the basal ganglia and, in particular, the putamen in rule-based category learning.

Neuron Activity in the Monkey Striatum of Identifies Integration Sequential Actions into Functional Blocks

Spike activity in monkey striatum (putamen) neurons was recorded during the performance of a complex multistep operant task. Tonic responses propagating beyond a single action were recorded, along with phasic responses seen within a given action. The tonic type of response was recorded in 132 of 148 cells. Only 11 of these neurons showed exclusively this type of activity. The beginnings and ends of tonic responses were generally associated with key moments in the behavior, corresponding to the triggering and completion of immediate aims during the performance of the behavioral program as a whole. These results provide evidence that the role of the striatum is not limited to controlling single sequentially performed actions, but spreads to the whole structure of a behavioral act.

Decoding of path-guided apparent motion from neural ensembles in posterior parietal cortex

We compared quantitatively the psychometric capacity of human subjects to detect path-guided apparent motion (PAM) and the accuracy of cell ensembles in area 7a to code the same type of stimuli. Nine human subjects performed a detection task of PAM. They were instructed to indicate with a key-press whether they perceived a circularly moving object when five stimuli were flashed successively at the vertices of a regular pentagon. The stimuli were presented along a low contrast circular path with one of 33 speeds (150-600 degrees /s). The average psychometric curve revealed that the threshold for PAM detection was 314 degrees /s. The minimum and maximum thresholds for individual subjects were 277 degrees and 378 degrees /s, respectively. In addition, the activity of cells in area 7a that were modulated by the stimulus position in real or apparent motion was used in a multivariate linear regression analysis to recover the stimulus position over time. Real stimulus motion was decoded successfully from neural ensemble activity at all speeds. In contrast, the decoding of PAM was poor at low stimulus speeds but improved markedly above 300 degrees /s: in fact, this was very close to the threshold above for human subjects to perceive continuous stimulus motion in this condition. These results suggest that the posterior parietal cortex is part of a high-level system that is directly involved in the dynamic representation of complex motion.

Anteromedial temporal cortex supports fine-grained differentiation among objects

Patients with damage to left anteromedial temporal cortex often show a striking deficit: they fail to recognize animals and other living things. This failure of recognition presents an important challenge to theories of the neural representation of conceptual knowledge. Here we propose that this lesion-behaviour association arises because polymodal neurons in anteromedial temporal cortex integrate simple features into complex feature conjunctions, providing the neural infrastructure for differentiating among objects.

Cortical activation during a spatiotemporal tactile comparison task

Tactile sensory memory is needed to infer shape or motion from the spatiotemporal pattern of sensory input during manual exploration. Here we applied triplets of pressure pulses to the fingertips of subjects who were asked to respond when successive triplets were the same (COMPARE task) or when a particular stimulus was included in a triplet (CONTROL task). Stimulus sequences (30 s) alternated with rest blocks (30 s) and functional magnetic resonance images (fMRIs) were acquired in a 1.5-T scanner. During the COMPARE task, we found enhanced activation in inferior parietal cortex, supplementary motor area (SMA), and right dorsolateral prefrontal cortex (DLPFC). Activation of DLPFC is likely to be related to the attempt to memorize the stimulus sequences and activations of SMA and inferior parietal cortex to the analysis of temporospatial tactile patterns and, more generally, to guidance of haptic exploration. In addition, task-specific activation was seen in anterior cingulate gyrus, possibly related to the high mental effort required by the comparison task. Our rhythmic tactile stimulus as such, without any task-specific enhancement, activated also left cerebellum and (mainly left) putamen, supporting the idea that these structures are related to perception of temporal order of tactile stimuli.

Flutter discrimination: neural codes, perception, memory and decision making

Recent studies combining psychophysical and neurophysiological experiments in behaving monkeys have provided new insights into how several cortical areas integrate efforts to solve a vibrotactile discrimination task. In particular, these studies have addressed how neural codes are related to perception, working memory and decision making in this model. The primary somatosensory cortex drives higher cortical areas where past and current sensory information are combined, such that a comparison of the two evolves into a behavioural decision. These and other observations in visual tasks indicate that decisions emerge from highly-distributed processes in which the details of a scheduled motor plan are gradually specified by sensory information.

From sensation to action

Key to understanding somatosensation is the form of how the mechanical stimuli are represented in the evoked neuronal activity of the brain. Here, we focus on studies that address the question of which components of the evoked neuronal activity in the somatosensory system represent the stimulus features. We review experiments that probe whether these neuronal representations are essential to somatosensation. We also discuss recent results that suggest how the somatosensory stimuli are represented in the brain during short-term memory. Finally, we review data that show the neuronal correlates of a decision during somatosensory perception.

Exploring the cortical evidence of a sensory-discrimination process

Humans and monkeys have similar abilities to discriminate the difference in frequency between two consecutive mechanical vibrations applied to their fingertips. This task can be conceived as a chain of neural operations: encoding the two consecutive stimuli, maintaining the first stimulus in working memory, comparing the second stimulus with the memory trace left by the first stimulus and communicating the result of the comparison to the motor apparatus. We studied this chain of neural operations by recording and manipulating neurons from different areas of the cerebral cortex while monkeys performed the task. The results indicate that neurons of the primary somatosensory cortex (S1) generate a neural representation of vibrotactile stimuli which correlates closely with psychophysical performance. Discrimination based on microstimulation patterns injected into clusters of S1 neurons is indistinguishable from that produced by natural stimuli. Neurons from the secondary somatosensory cortex (S2), prefrontal cortex and medial premotor cortex (MPC) display at different times the trace of the first stimulus during the working-memory component of the task. Neurons from S2 and MPC appear to show the comparison between the two stimuli and correlate with the behavioural decisions. These neural operations may contribute to the sensory-discrimination process studied here.

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.

Neural correlates for roughness choice in monkey second somatosensory cortex (SII)

This experiment explored the relationship between neural firing patterns in second somatosensory cortex (SII) and decisions about roughness of tactile gratings. Neural and behavioral data were acquired while monkeys made dichotomous roughness classifications of pairs of gratings that differed in groove width (1.07 vs. 1.90 and 1.42 vs. 2.53 mm). A computer-controlled device delivered the gratings to a single immobilized finger pad. In one set of experiments, three levels of contact force (30, 60, and 90 g) were assigned to these gratings at random. In another set of experiments, three levels of scanning speed (40, 80, and 120 mm/s) were assigned to these gratings at random. Groove width was the intended variable for roughness. Force variation disrupted the monkeys' groove-width (roughness) classifications more than did speed variation. A sample of 32 SII cells showed correlated changes in firing (positive or negative effects of both variables) when groove width and force increased. While these cells were recorded, the monkeys made roughness classification errors, confusing wide groove-width gratings at low force with narrow groove-width gratings at high force. Three-dimensional plots show how some combinations of groove width and force perturbed the monkeys' trial-wise classifications of grating roughness. Psychometric functions show that errors occurred when firing rates failed to distinguish gratings. A possible interpretation is that when asked to classify grating roughness, the monkeys based classifications on the firing rates of a subset of roughness-sensitive cells in SII. Results support human psychophysical data and extend the roughness range of a model of the effects of groove width and force on roughness. One monkey's SII neural sample (21 cells) showed significant correlation between firing rate response functions for groove width and speed (both correlations either positive or negative). Only that monkey showed a statistically significant interaction between groove width and speed on roughness classification performance. This additional finding adds weight to the argument that SII cell firing rates influenced monkey roughness classifications.

Touch and go: decision-making mechanisms in somatosensation

A complex sequence of neural events unfolds between sensory receptor activation and motor activity. To understand the underlying decision-making mechanisms linking somatic sensation and action, we ask what components of the neural activity evoked by a stimulus are directly related to psychophysical performance, and how are they related. We find that single-neuron responses in primary and secondary somatosensory cortices account for the observed performance of monkeys in vibrotactile discrimination tasks, and that neuronal and behavioral responses covary in single trials. This sensory activity, which provides input to memory and decision-making mechanisms, is modulated by attention and behavioral context, and microstimulation experiments indicate that it may trigger normal perceptual experiences. Responses recorded in motor areas seem to reflect the output of decision-making operations, which suggests that the ability to make decisions occurs at the sensory-motor interface.

Binding personal and peripersonal space: evidence from tactile extinction

Behavioral and neurophysiological studies suggest that the brain constructs different representations of space. Among these representations are personal and peripersonal space. Personal space refers to the space occupied by our bodies. Peripersonal space refers to the space surrounding our bodies, which can be reached by our limbs. How these two representations are bound to give a unified sense of space in which humans act is not clear. We tested 10 patients with tactile extinction to investigate this issue. Tactile extinction is an attentional disorder in which patients are unaware of being touched on their contralesional limb if they are also touched simultaneously on their ipsilesional limb. We hypothesized that mechanisms that bind personal and peripersonal representations would improve these patients' awareness of being touched on their contralesional limbs. Visual--tactile integration and intentional movements were considered candidate mechanisms. Patients were more likely to be aware of contralesional touch when looking towards their contralesional limb than when looking towards their ipsilesional limb, and when actively moving on tactile probes than when receiving tactile stimuli passively. The improved awareness of being touched on the contralesional limb under these conditions suggests that cross-sensory and sensorimotor integration help bind personal and peripersonal space.

Somatosensation: Touching the mind's fingers

Whether mental operations can be reduced to the biological properties of the brain has intrigued scientists and philosophers alike for millennia. New microstimulation experiments on awake, behaving monkeys establish causality between activity of specialized cortical neurons and a controlled behavior.

Role of [corrected] nigrostriatal dopamine system in learning to perform sequential motor tasks in a predictive manner

Neurons in the primate striatum and the substantia nigra pars compacta change their firing patterns during sensory-motor learning. To study the consequences of nigrostriatal dopamine depletion for learning and memory of motor sequences, we used a neurotoxin, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), to deplete dopamine unilaterally in the striatum of macaque monkeys either before or after training them on sequential push-button motor tasks. We compared the monkeys' performance with the arms ipsilateral and contralateral to dopamine depletion. During training and retraining on the tasks, we measured initial and serial movement times and reaction times for the push button movements, electromyographic patterns of arm and orofacial muscle activity during button pushing and reward licking, and saccadic eye movements during the button push sequences. With the arm ipsilateral to the side of dopamine depletion, each monkey showed progressive shortening of movement times and initial and serial reaction times, and each developed consistent strategies of hand-orofacial and hand-eye coordination in which single button push movements were linked efficiently to succeeding movements so that performance of the whole sequence became predictive. These patterns did not develop for contralateral arm performance in this monkey treated with MPTP before training. With the arm contralateral to dopamine depletion, the monkey showed significant quantitative deficits in all parameters measured except initial reaction times. Movement times and serial reaction times were longer than those for the ipsilateral arm; anticipatory saccadic eye movements were not well time-locked to individual button pushes made with the contralateral hand; and push and licking movements were not smoothly coordinated. This monkey further showed striking differences in performance when using the ipsilateral and contralateral arms in switch trial tests in which reward was delivered unexpectedly one button early. He continued to make movements to the previously rewarded button with the ipsilateral arm but showed no such automatic movements when he used his contralateral arm. For the monkey treated with MPTP after training, performance on the push-button task was skilled for both arms before dopamine depletion, but the unilateral dopamine depletion produced deficits in contralateral arm performance for all parameters measured, again excepting initial reaction times. With retraining, however, his performance with the contralateral arm improved. We conclude that the striatum and its nigrostriatal afferents function in the initial learning underlying performance of sequences of movements as single motor programs. The nigrostriatal system also operates during the retrieval of these programs once learning is accomplished, but lesions of the nigrostriatal system spare the ability to relearn the previously acquired programs.

Sensing and deciding in the somatosensory system

Combined psychophysical and neurophysiological experiments have revealed some of the neural codes associated with perception and processing of tactile information. Recently, intracortical microstimulation was used to demonstrate a causal link between primary cortical activity and perception. Evidence for a subsequent link, between a sensory decision process and its expression as a movement, has been found in motor areas.

Anesthetics eliminate somatosensory-evoked discharges of neurons in the somatotopically organized sensorimotor striatum of the rat

The somatotopic organization of the lateral striatum has been demonstrated by anatomical studies of corticostriatal projections from somatosensory and motor cortices and by single-cell recordings in awake animals. The functional organization in the rat, characterized thus far in the freely moving rat preparation, could be mapped more precisely if a stereotaxic, and possibly an anesthetized, preparation could be used. Because striatal discharges evoked by innocuous somatosensory stimulation are used in mapping, this study tested whether such discharges can be observed during anesthesia, encouraged by responsiveness during anesthesia in somatosensory cortical layers projecting to the striatum. Electrode tracks through lateral striatum of anesthetized rats (pentobarbital or ketamine) revealed spontaneously discharging neurons but no discharges evoked by somatosensory examination (passive manipulation and cutaneous stimulation of 14 body parts). Similar tracks in chronically implanted rats showed evoked firing at numerous sites during wakefulness but not during anesthesia (pentobarbital or urethane). Comparisons of the activity of individual neurons between wakefulness and anesthesia showed that pentobarbital, ketamine, chloral hydrate, urethane, or metofane eliminated evoked firing and suppressed spontaneous firing. Recovery time was greater for neural than for behavioral measures. Thus, mapping as proposed is ruled out, and more importantly, the data show that somatotopically organized lateral striatal neurons stop discharging in response to natural stimulation during anesthesia. Available data indicate they do not reach threshold in response to depolarizations produced by glutamatergic corticostriatal synaptic transmission projected from the somatosensory cortex. These data and demonstrations of anesthetic-induced imbalances in most striatal neurotransmitters emphasize that many results regarding striatal physiology and pharmacology during anesthesia cannot be extrapolated to behavioral conditions, thus indicating the need for more empirical testing in conscious animals.