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The midcingulate cortex and temporal integration
Abstract
The ability to integrate information across time at multiple timescales is a vital element of adaptive behavior, because it provides the capacity to link events separated in time, extract useful information from previous events and actions, and to construct plans for behavior over time. Here we make the argument that this information integration capacity is a central function of the midcingulate cortex (MCC), by reviewing the anatomical, intrinsic network, neurophysiological, and behavioral properties of MCC. The MCC is the region of the medial wall situated dorsal to the corpus callosum and sometimes referred to as dACC. It is positioned within the densely connected core network of the primate brain, with a rich diversity of cognitive, somatomotor and autonomic connections. Furthermore, the MCC shows strong local network inhibition which appears to control the metastability of the region—an established feature of many cortical networks in which the neural dynamics move through a series of quasi-stationary states. We propose that the strong local inhibition in MCC leads to particularly long dynamic state durations, and so less frequent transitions. Apparently as a result of these anatomical features and synaptic and ionic determinants, the MCC cells display the longest neuronal timescales among a range of recorded cortical areas. We conclude that the anatomical position, intrinsic properties, and local network interactions of MCC make it a uniquely positioned cortical area to perform the integration of diverse information over time that is necessary for behavioral adaptation.
Previous studies have reported sex differences in altered brain function in patients with chronic insomnia (CI). However, sex-related alterations in brain morphology have rarely been investigated. This study aimed to investigate sex-specific grey matter (GM) alterations in patients with CI and to examine the relationship between GM alterations and neuropsychological assessments. Ninety-three (65 females and 28 males) patients and 78 healthy (50 females and 28 males) controls were recruited. Structural magnetic resonance imaging data were analysed using voxel-based morphometry to test for interactions between sex and diagnosis. Spearman’s correlation was used to assess the associations among structure, disease duration, and sleep-, mood-, and cognition-related assessments. Males with CI showed reduced GM volume in the left inferior parietal lobe, left middle cingulate cortex, and right supramarginal gyrus. Females with CI showed increased GM volume in the right Rolandic operculum. Moreover, mood-related assessments were negatively correlated with GM volumes in the right supramarginal gyrus and left inferior parietal lobe in the male patients, and cognitive-related assessments were positively correlated with GM volumes in the Rolandic operculum in the female patients. Our findings indicate sex-specific alterations in brain morphology in CI, thereby broadening our understanding of sex differences in CI and potentially providing complementary evidence for the development of more effective therapies and individual treatments.
There is ample behavioral evidence that others' mere presence can affect any behavior in human and non-human animals, generally facilitating the expression of mastered responses while impairing the acquisition of novel ones. Much less is known about i) how the brain orchestrates the modulation of such a wide array of behaviors by others' presence and ii) when these neural underpinnings mature during development. To address these issues, fMRI data were collected in children and adults alternately observed and unobserved by a familiar peer. Subjects performed a numerosity comparison task and a phonological comparison task. While the former involves number-processing brain areas, the latter involves language-processing areas. Consistent with previous behavioral findings, adults' and children's performance improved in both tasks when observed by a peer. Across all participants, task-specific brain regions showed no reliable change in activity under peer observation. Rather, we found task-independent changes in domain-general brain regions typically involved in mentalizing, reward, and attention. Bayesian analyses singled out the attention network as the exception to the close child-adult resemblance of peer observation neural substrates. These findings suggest that i) social facilitation of some human education-related skills is primarily orchestrated by domain-general brain networks, rather than by task-selective substrates, and ii) apart from attention, peer presence neural processing is largely mature in children.
Behavioral adaptations are triggered by different constraints given by rules, and are informed by outcomes, or motivational changes. Neural activity in multiple frontal areas is modulated during behavioral adaptations but the source of these modulations and the nature of the mechanisms involved are unclear. Here we tested how different variables related to changes in task performance and to behavioral adaptation impact the amplitude of event-related local field potentials (LFP) in the lateral prefrontal cortex and midcingulate cortex of male rhesus macaques. We found that the behavioral task used induced consistently different types of performance modulation: in relation to task difficulty (imposed by the experimental setup), to successes and errors, and to the time spent in the task. Difficulty had a significant effect on monkeys’ accuracy and reaction times. Interestingly, there is also a strong interaction between difficulty and trial success on the reaction times variation. However, LFP modulations were mostly related to reaction times, touch position, feedback valence and time-in-session, with little, if any, effect of difficulty. Hence difficulty modulated performance but not LFP activity. This suggests that in our experimental design, execution, regulation and motivation-related factors are the main factors influencing medial and lateral frontal activity.
Significance Statement:
Adapting decisions might be determined by several mechanisms and might be driven by motivational factors and/or factors inherent to the task at hand. Multiple frontal areas contribute to behavioral adaptations. One current challenge is to understand which information they process contributes to behavioral changes. Diverging views have emerged on whether task demands, like the decision difficulty, or factors linked to incentives to adapt, are driving frontal activity. Here we show that task difficulty had a strong effect on performance (accuracy and reaction times) but little effect on LFP recorded in monkey lateral prefrontal and midcingulate cortex. However, information related to actions, outcome valence and time-in-session had major influences. Thus, task difficulty modulated performance but not LFP activity in frontal areas.
Significance
The brain exhibits a tremendous amount of heterogeneity, and to make sense of this seemingly random system neuroscientists have explored various ideas to organize it into distinct areas, each performing certain computations. One such idea is the timescale at which neural response fluctuates. Here, we developed a comprehensive method to estimate multiple timescales in neural response and link these timescales to processing of task-relevant signals and behavioral adjustments. We found multiple types of timescales that increase across cortical areas in parallel while being independent of each other and of selectivity to task-relevant signals. Our results suggest that there are multiple independent mechanisms underlying generations of neural dynamics on different timescales.
Optimal decision-making requires that stimulus-value associations are kept up to date by constantly comparing the expected value of a stimulus with its experienced outcome. To do this, value information must be held in mind when a stimulus and outcome are separated in time. However, little is known about the neural mechanisms of working memory (WM) for value. Contradicting theories have suggested WM requires either persistent or transient neuronal activity, with stable or dynamic representations respectively. To test these hypotheses, we recorded neuronal activity in the orbitofrontal and anterior cingulate cortex of two monkeys performing a valuation task. We found that features of all hypotheses were simultaneously present in prefrontal activity, and no single hypothesis was exclusively supported. Instead, mixed dynamics supported robust, time invariant value representations while also encoding the information in a temporally specific manner. We suggest that this hybrid coding is a critical mechanism supporting flexible cognitive abilities.
The ability to adjust one's behavioral strategy in complex environments is at the core of cognition. Doing so efficiently requires monitoring the reliability of the ongoing strategy and switching away from it to evaluate alternatives when appropriate. Studies in humans and non-human primates have uncovered signals in the anterior cingulate cortex (ACC) that track the pressure to switch away from the ongoing strategy, and others that relate to the pursuit of alternatives. However, whether these signals underlie computations that actually underpin strategy switching, or merely reflect tracking of related variables remains unclear. Here we provide causal evidence that rodent ACC actively arbitrates between persisting with ongoing behavioral choice and switching away temporarily to re-evaluate alternatives. Furthermore, by individually perturbing distinct output pathways, we establish that the two associated computations-whether to switch away from the current choice, and the pursuit of alternatives-are segregated within ACC micro-circuitry.
In the primate brain, a set of areas in the ventrolateral frontal (VLF) cortex and the dorsomedial frontal (DMF) cortex appear to control vocalizations. The basic role of this network in the human brain and how it may have evolved to enable complex speech remain unknown. In the present functional neuroimaging study of the human brain, a multidomain protocol was utilized to investigate the roles of the various areas that comprise the VLF–DMF network in learning rule-based cognitive selections between different types of motor actions: manual, orofacial, nonspeech vocal, and speech vocal actions. Ventrolateral area 44 (a key component of the Broca’s language production region in the human brain) is involved in the cognitive selection of orofacial, as well as, speech and nonspeech vocal responses; and the midcingulate cortex is involved in the analysis of speech and nonspeech vocal feedback driving adaptation of these responses. By contrast, the cognitive selection of speech vocal information requires this former network and the additional recruitment of area 45 and the presupplementary motor area. We propose that the basic function expressed by the VLF–DMF network is to exert cognitive control of orofacial and vocal acts and, in the language dominant hemisphere of the human brain, has been adapted to serve higher speech function. These results pave the way to understand the potential changes that could have occurred in this network across primate evolution to enable speech production.
We investigated two-attribute, two-alternative decision-making in a hierarchical neural network with three layers: an input layer encoding choice alternative attribute values; an intermediate layer of modules processing separate attributes; and a choice layer producing the decision. Depending on intermediate layer excitatory-inhibitory (E/I) tone, the network displays three distinct regimes characterized by linear (I), convex (II) or concave (III) choice indifference curves. In regimes I and II, each option's attribute information is additively integrated. To maximize reward at low environmental uncertainty, the system should operate in regime I. At high environmental uncertainty, reward maximization is achieved in regime III, with each attribute module selecting a favored alternative, and the ultimate decision based upon comparison between outputs of attribute processing modules. We then use these principles to examine multi-attribute decisions with autism-related deficits in E/I balance, leading to predictions of different choice patterns and overall performance between autism and neurotypicals.
Which regions of the cerebral cortex are the origin of descending commands that influence internal organs? We used transneuronal transport of rabies virus in monkeys and rats to identify regions of cerebral cortex that have multisynaptic connections with a major sympathetic effector, the adrenal medulla. In rats, we also examined multisynaptic connections with the kidney. In monkeys, the cortical influence over the adrenal medulla originates from 3 distinct networks that are involved in movement, cognition, and affect. Each of these networks has a human equivalent. The largest influence originates from a motor network that includes all 7 motor areas in the frontal lobe. These motor areas are involved in all aspects of skeletomotor control, from response selection to motor preparation and movement execution. The motor areas provide a link between body movement and the modulation of stress. The cognitive and affective networks are located in regions of cingulate cortex. They provide a link between how we think and feel and the function of the adrenal medulla. Together, the 3 networks can mediate the effects of stress and depression on organ function and provide a concrete neural substrate for some psychosomatic illnesses. In rats, cortical influences over the adrenal medulla and the kidney originate mainly from 2 motor areas and adjacent somatosensory cortex. The cognitive and affective networks, present in monkeys, are largely absent in rats. Thus, nonhuman primate research is essential to understand the neural substrate that links cognition and affect to the function of internal organs.
Humans and other animals often show a strong desire to know the uncertain rewards their future has in store, even when they cannot use this information to influence the outcome. However, it is unknown how the brain predicts opportunities to gain information and motivates this information-seeking behavior. Here we show that neurons in a network of interconnected subregions of primate anterior cingulate cortex and basal ganglia predict the moment of gaining information about uncertain rewards. Spontaneous increases in their information prediction signals are followed by gaze shifts toward objects associated with resolving uncertainty, and pharmacologically disrupting this network reduces the motivation to seek information. These findings demonstrate a cortico-basal ganglia mechanism responsible for motivating actions to resolve uncertainty by seeking knowledge about the future. Animals resolve uncertainty by seeking knowledge about the future. How the brain controls this is unclear. The authors show that a network including primate anterior cingulate cortex and basal ganglia encodes opportunities to gain information about uncertain rewards and mediates information seeking.
The dorsal anterior cingulate cortex (dACC) and lateral prefrontal cortex (lPFC) of the non-human primate show neural firing correlations and synchronize at theta and beta frequencies during the monitoring and shifting of attention. These functional interactions might be based on synaptic connectivity that is equally efficacious in both directions, but it might be that there are systematic asymmetries in connectivity consistent with reports of more effective inhibition within the dACC than lPFC, or with a preponderance of dACC projections synapsing onto inhibitory neurons in the lPFC. Here, we tested effective dACC-lPFC connectivity in awake monkeys and report systematic asymmetries in the temporal patterning and latencies of effective connectivity as measured using electrical microstimulation. We found that dACC stimulation-triggered evoked fields (EFPs) were more likely to be multiphasic in the lPFC than in the reverse direction, with a large proportion of connections showing 2–4 inflection points resembling resonance in the 20–30 Hz beta frequency range. Stimulation of dACC → lPFC resulted, on average, in shorter-latency EFPs than lPFC → dACC. Overall, latencies and connectivity strength varied more than twofold depending on the precise anterior-to-posterior location of the connections. These findings reveal systematic asymmetries in effective connectivity between dACC and lPFC in the awake non-human primate and document the spatial and temporal patchiness of effective synaptic connections. We discuss that our results suggest that measuring effective connectivity profiles will be essential for understanding how asymmetries in local synaptic efficacy and connectivity translate into functional neuronal interactions during adaptive, goal-directed behavior.
Nonhuman primates have proven to be a valuable animal model for exploring neuronal mechanisms of cognitive control. One important aspect of executive control is the ability to switch from one task to another, and task-switching paradigms have often been used in human volunteers to uncover the underlying neuronal processes. To date, however, no study has investigated task-switching paradigms in nonhuman primates during functional magnetic resonance imaging (fMRI). We trained two rhesus macaques to switch between arm movement, eye movement, and passive fixation tasks during fMRI. Similar to results obtained in human volunteers, task switching elicits increased fMRI activations in prefrontal cortex, anterior cingulate cortex, orbitofrontal cortex, and caudate nucleus. Our results indicate that the macaque monkey is a reliable model with which to investigate higher-order cognitive functioning such as task switching. As such, these results can pave the way for a detailed investigation of the neural basis of complex human behavior.
SIGNIFICANCE STATEMENT Task switching is an important aspect of cognitive control, and task-switching paradigms have often been used to investigate higher-order executive functioning in human volunteers. We used a task-switching paradigm in the nonhuman primate during fMRI and found increased activation mainly in prefrontal areas (46, 45, frontal eye field, and anterior cingulate), in orbitofrontal area 12, and in the caudate nucleus. These data fit surprisingly well with previous human imaging data, proving that the monkey is an excellent model to study task switching with high spatiotemporal resolution tools that are currently not applicable in humans. As such, our results pave the way for a detailed interrogation of regions performing similar executive functions in humans and monkeys.
Naturalistic decision-making typically involves sequential deployment of attention to choice alternatives to gather information before a decision is made. Attention filters how information enters decision circuits, thus implying that attentional control may shape how decision computations unfold. We recorded neuronal activity from three subregions of the prefrontal cortex (PFC) while monkeys performed an attention-guided decision-making task. From the first saccade to decision-relevant information, a triple dissociation of decision- and attention-related computations emerged in parallel across PFC subregions. During subsequent saccades, orbitofrontal cortex activity reflected the value comparison between currently and previously attended information. In contrast, the anterior cingulate cortex carried several signals reflecting belief updating in light of newly attended information, the integration of evidence to a decision bound and an emerging plan for what action to choose. Our findings show how anatomically dissociable PFC representations evolve during attention-guided information search, supporting computations critical for value-guided choice.
Recent experiments demonstrate substantial volatility of excitatory connectivity in the absence of any learning. This challenges the hypothesis that stable synaptic connections are necessary for long-term maintenance of acquired information. Here we measure ongoing synaptic volatility and use theoretical modeling to study its consequences on cortical dynamics. We show that in the balanced cortex, patterns of neural activity are primarily determined by inhibitory connectivity, despite the fact that most synapses and neurons are excitatory. Similarly, we show that the inhibitory network is more effective in storing memory patterns than the excitatory one. As a result, network activity is robust to ongoing volatility of excitatory synapses, as long as this volatility does not disrupt the balance between excitation and inhibition. We thus hypothesize that inhibitory connectivity, rather than excitatory, controls the maintenance and loss of information over long periods of time in the volatile cortex.
Competing accounts propose that working memory (WM) is subserved either by persistent activity in single neurons or by dynamic (time-varying) activity across a neural population. Here, we compare these hypotheses across four regions of prefrontal cortex (PFC) in an oculomotor-delayed-response task, where an intervening cue indicated the reward available for a correct saccade. WM representations were strongest in ventrolateral PFC neurons with higher intrinsic temporal stability (time-constant). At the population-level, although a stable mnemonic state was reached during the delay, this tuning geometry was reversed relative to cue-period selectivity, and was disrupted by the reward cue. Single-neuron analysis revealed many neurons switched to coding reward, rather than maintaining task-relevant spatial selectivity until saccade. These results imply WM is fulfilled by dynamic, population-level activity within high time-constant neurons. Rather than persistent activity supporting stable mnemonic representations that bridge subsequent salient stimuli, PFC neurons may stabilise a dynamic population-level process supporting WM.
Working memory (WM) is characterized by the ability to maintain stable representations over time; however, neural activity associated with WM maintenance can be highly dynamic. We explore whether complex population coding dynamics during WM relate to the intrinsic temporal properties of single neurons in lateral prefrontal cortex (lPFC), the frontal eye fields (FEF), and lateral intraparietal cortex (LIP) of two monkeys (Macaca mulatta). We find that cells with short timescales carry memory information relatively early during memory encoding in lPFC; whereas long-timescale cells play a greater role later during processing, dominating coding in the delay period. We also observe a link between functional connectivity at rest and the intrinsic timescale in FEF and LIP. Our results indicate that individual differences in the temporal processing capacity predict complex neuronal dynamics during WM, ranging from rapid dynamic encoding of stimuli to slower, but stable, maintenance of mnemonic information.
Optimal decision-making is based on integrating information from several dimensions of decisional space (e.g., reward expectation, cost estimation, effort exertion). Despite considerable empirical and theoretical efforts, the computational and neural bases of such multidimensional integration have remained largely elusive. Here we propose that the current theoretical stalemate may be broken by considering the computational properties of a cortical-subcortical circuit involving the dorsal anterior cingulate cortex (dACC) and the brainstem neuromodulatory nuclei: ventral tegmental area (VTA) and locus coeruleus (LC). From this perspective, the dACC optimizes decisions about stimuli and actions, and using the same computational machinery, it also modulates cortical functions (meta-learning), via neuromodulatory control (VTA and LC). We implemented this theory in a novel neuro-computational model–the Reinforcement Meta Learner (RML). We outline how the RML captures critical empirical findings from an unprecedented range of theoretical domains, and parsimoniously integrates various previous proposals on dACC functioning.
The cingulate cortex is a mosaic of different anatomical fields, whose functional characterization is still a matter of debate. In humans, one method that may provide useful insights on the role of the different cingulate regions, and to tackle the issue of the functional differences between its anterior, middle and posterior subsectors, is intracortical electrical stimulation. While previous reports showed that a variety of integrated behaviours could be elicited by stimulating the midcingulate cortex, little is known about the effects of the electrical stimulation of anterior and posterior cingulate regions. Moreover, the internal arrangement of different behaviours within the midcingulate cortex is still unknown. In the present study, we extended previous stimulation studies by retrospectively analysing all the clinical manifestations induced by intracerebral high frequency electrical stimulation (50 Hz, pulse width: 1 ms, 5 s, current intensity: average intensity of 2.7 ± 0.7 mA, biphasic) of the entire cingulate cortex in a cohort of 329 drug-resistant epileptic patients (1789 stimulation sites) undergoing stereo-electroencephalography for a presurgical evaluation. The large number of patients, on one hand, and the accurate multimodal image-based localization of stereo-electroencephalography electrodes, on the other hand, allowed us to assign specific functional properties to modern anatomical subdivisions of the cingulate cortex. Behavioural or subjective responses were elicited from the 32.3% of all cingulate sites, mainly located in the pregenual and midcingulate regions. We found clear functional differences between the pregenual part of the cingulate cortex, hosting the majority of emotional, interoceptive and autonomic responses, and the anterior midcingulate sector, controlling the majority of all complex motor behaviours. Particularly interesting was the 'actotopic' organization of the anterior midcingulate sector, arranged along the ventro-dorsal axis: (i) whole-body behaviours directed to the extra-personal space, such as getting-up impulses, were elicited ventrally, close to the corpus callosum; (ii) hand actions in the peripersonal space were evoked by the stimulation of the intermediate position; and (iii) body-directed actions were induced by the stimulation of the dorsal branch of the cingulate sulcus. The caudal part of the midcingulate cortex and the posterior cingulate cortex were, in contrast, poorly excitable, and mainly devoted to sensory modalities. In particular, the caudal part of the midcingulate cortex hosted the majority of vestibular responses, while posterior cingulate cortex was the principal recipient of visual effects. We will discuss our data in the light of current controversies on the role of the cingulate cortex in cognition and emotion.
Comparing the brains of related species faces the challenges of establishing homologies whilst accommodating evolutionary specializations. Here we propose a general framework for understanding similarities and differences between the brains of primates. The approach uses white matter blueprints of the whole cortex based on a set of white matter tracts that can be anatomically matched across species. The blueprints provide a common reference space that allows us to navigate between brains of different species, identify homologous cortical areas, or to transform whole cortical maps from one species to the other. Specializations are cast within this framework as deviations between the species’ blueprints. We illustrate how this approach can be used to compare human and macaque brains.
The dorsal anterior cingulate cortex (dACC) plays crucial roles in monitoring the outcome of a choice and adjusting a subsequent choice behavior based on the outcome information. In the present study, we investigated how different types of dACC neurons, that is, putative pyramidal neurons and putative inhibitory interneurons, contribute to these processes. We analyzed single-unit database obtained from the dACC in monkeys performing a reversal learning task. The monkey was required to adjust choice behavior from past outcome experiences. Depending on their action potential waveforms, the recorded neurons were classified into putative pyramidal neurons and putative inhibitory interneurons. We found that these neurons do not equally contribute to outcome monitoring and behavioral adjustment. Although both neuron types evenly responded to the current outcome, a larger proportion of putative inhibitory interneurons than putative pyramidal neurons stored the information about the past outcome. The putative inhibitory interneurons further represented choice-related signals more frequently, such as whether the monkey would shift the last choice to an alternative at the next choice opportunity. Our findings suggest that putative inhibitory interneurons, which are thought not to project to brain areas outside the dACC, preferentially transmit signals that would adjust choice behavior based on past outcome experiences.
According to contemporary views, the lateral frontal cortex is organized along a rostro-caudal functional axis with increasingly complex cognitive/behavioral control implemented rostrally, and increasingly detailed motor control implemented caudally. Whether the medial frontal cortex follows the same organization remains to be elucidated. To address this issue, the functional connectivity of the 3 cingulate motor areas (CMAs) in the human brain with the lateral frontal cortex was investigated. First, the CMAs and their representations of hand, tongue, and eye movements were mapped via task-related functional magnetic resonance imaging (fMRI). Second, using resting-state fMRI, their functional connectivity with lateral prefrontal and lateral motor cortical regions of interest (ROIs) were examined. Importantly, the above analyses were conducted at the single-subject level to account for variability in individual cingulate morphology. The results demonstrated a rostro-caudal functional organization of the CMAs in the human brain that parallels that in the lateral frontal cortex: the rostral CMA has stronger functional connectivity with prefrontal regions and weaker connectivity with motor regions; conversely, the more caudal CMAs have weaker prefrontal and stronger motor connectivity. Connectivity patterns of the hand, tongue and eye representations within the CMAs are consistent with that of their parent CMAs. The parallel rostral-to-caudal functional organization observed in the medial and lateral frontal cortex could likely contribute to different hierarchies of cognitive-motor control.
Dorsal anterior cingulate cortex (dACC) mediates updating and maintenance of cognitive models of the world used to drive adaptive reward-guided behavior. We investigated the neurochemical underpinnings of this process. We used magnetic resonance spectroscopy in humans, to measure levels of glutamate and GABA in dACC. We examined their relationship to neural signals in dACC, measured with fMRI, and cognitive task performance. Both inhibitory and excitatory neurotransmitters in dACC were predictive of the strength of neural signals in dACC and behavioral adaptation. Glutamate levels were correlated, first, with stronger neural activity representing information to be learnt about the tasks' costs and benefits and, second, greater use of this information in the guidance of behavior. GABA levels were negatively correlated with the same neural signals and the same indices of behavioral influence. Our results suggest that glutamate and GABA in dACC affect the encoding and use of past experiences to guide behavior.
Decisions are based on value expectations derived from experience. We show that dorsal anterior cingulate cortex and three other brain regions hold multiple representations of choice value based on different timescales of experience organized in terms of systematic gradients across the cortex. Some parts of each area represent value estimates based on recent reward experience while others represent value estimates based on experience over the longer term. The value estimates within these areas interact with one another according to their temporal scaling. Some aspects of the representations change dynamically as the environment changes. The spectrum of value estimates may act as a flexible selection mechanism for combining experience-derived value information with other aspects of value to allow flexible and adaptive decisions in changing environments.
Population-level theta and beta band activity in anterior cingulate and prefrontal cortices (ACC/PFC) are prominent signatures of self-controlled, adaptive behaviors. But how these rhythmic activities are linked to cell-type specific activity has remained unclear. Here, we suggest such a cell-to-systems level linkage. We found that the rate of burst spiking events is enhanced particularly during attention states and that attention-specific burst spikes have a unique temporal relationship to local theta and beta band population-level activities. For the 5-10 Hz theta frequency range, bursts coincided with transient increases of local theta power relative to nonbursts, particularly for bursts of putative interneurons. For the 16-30 Hz beta frequency, bursts of putative interneurons phase synchronized stronger than nonbursts, and were associated with larger beta power modulation. In contrast, burst of putative pyramidal cells showed similar beta power modulation as nonbursts, but were accompanied by stronger beta power only when they occurred early in the beta cycle. These findings suggest that in the ACC/PFC during attention states, mechanisms underlying burst firing are intimately linked to narrow band population-level activities, providing a cell-type specific window into rhythmic inhibitory gating and the emergence of rhythmically coherent network states during goal directed behavior.
We measured the densities (fmol/mg protein) of 15 different receptors of various transmitter systems in the supragranular, granular and infragranular strata of 44 areas of visual, somatosensory, auditory and multimodal association systems of the human cerebral cortex. Receptor densities were obtained after labeling of the receptors using quantitative in vitro receptor autoradiography in human postmortem brains. The mean density of each receptor type over all cortical layers and of each of the three major strata varies between cortical regions. In a single cortical area, the multi-receptor fingerprints of its strata (i.e., polar plots, each visualizing the densities of multiple different receptor types in supragranular, granular or infragranular layers of the same cortical area) differ in shape and size indicating regional and laminar specific balances between the receptors. Furthermore, the three strata are clearly segregated into well definable clusters by their receptor fingerprints. Fingerprints of different cortical areas systematically vary between functional networks, and with the hierarchical levels within sensory systems. Primary sensory areas are clearly separated from all other cortical areas particularly by their very high muscarinic M2 and nicotinic α4β2 receptor densities, and to a lesser degree also by noradrenergic α2 and serotonergic 5-HT2 receptors. Early visual areas of the dorsal and ventral streams are segregated by their multi-receptor fingerprints. The results are discussed on the background of functional segregation, cortical hierarchies, microstructural types, and the horizontal (layers) and vertical (columns) organization in the cerebral cortex. We conclude that a cortical column is composed of segments, which can be assigned to the cortical strata. The segments differ by their patterns of multi-receptor balances, indicating different layer-specific signal processing mechanisms. Additionally, the differences between the strata-and area-specific fingerprints of the 44 areas reflect the segregation of the cerebral cortex into functionally and topographically definable groups of cortical areas (visual, auditory, somatosensory, limbic, motor), and reveals their hierarchical position (primary and unimodal (early) sensory to higher sensory and finally to multimodal association areas).
HighlightsDensities of transmitter receptors vary between areas of human cerebral cortex.
Multi-receptor fingerprints segregate cortical layers.
The densities of all examined receptor types together reach highest values in the supragranular stratum of all areas.
The lowest values are found in the infragranular stratum.
Multi-receptor fingerprints of entire areas and their layers segregate functional systems
Cortical types (primary sensory, motor, multimodal association) differ in their receptor fingerprints.
Anterior cingulate cortex (ACC) is thought to control a wide range of reward, punishment, and uncertainty-related behaviors. However, how it does so is unclear. Here, in a Pavlovian procedure in which monkeys displayed a diverse repertoire of reward-related, punishment-related, and uncertainty-related behaviors, we show that many ACC-neurons represent expected value and uncertainty in a valence-specific manner, signaling value or uncertainty predictions about either rewards or punishments. Other ACC-neurons signal prediction information about rewards and punishments by displaying excitation to both (rather than excitation to one and inhibition to the other). This diversity in valence representations may support the role of ACC in many behavioral states that are either enhanced by reward and punishment (e.g., vigilance) or specific to either reward or punishment (e.g., approach and avoidance). Also, this first demonstration of punishment-uncertainty signals in the brain suggests that ACC could be a target for the treatment of uncertainty-related disorders of mood.
The lateral prefrontal cortex (LPFC) and anterior cingulate cortex (ACC) of the primate play distinctive roles in the mediation of complex cognitive tasks. Compared with the LPFC, integration of information by the ACC can span longer timescales and requires stronger engagement of inhibitory processes. Here, we reveal the synaptic mechanism likely to underlie these differences using in vitro patchclamp recordings of synaptic events and multiscale imaging of synaptic markers in rhesus monkeys. Although excitatory synaptic signaling does not differ, the level of synaptic inhibition is much higher in ACC than LPFC layer 3 pyramidal neurons, with a significantly higher frequency (~6 ×) and longer duration of inhibitory synaptic currents. The number of inhibitory synapses and the ratio of cholecystokinin to parvalbumin-positive inhibitory inputs are also significantly higher in ACC compared with LPFC neurons. Therefore, inhibition is functionally and structurally more robust and diverse in ACC than in LPFC, resulting in a lower excitatory: inhibitory ratio and a greater dynamic range for signal integration and network oscillation by the ACC. These differences in inhibitory circuitry likely underlie the distinctive network dynamics in ACC and LPC during normal and pathological brain states.
Dopamine is thought to directly influence the neurophysiological mechanisms of both performance monitoring and cognitive control—two processes that are critically linked in the production of adapted behaviour. Changing dopamine levels are also thought to induce cognitive changes in several neurological and psychiatric conditions. But the working model of this system as a whole remains untested. Specifically, although many researchers assume that changing dopamine levels modify neurophysiological mechanisms and their markers in frontal cortex, and that this in turn leads to cognitive changes, this causal chain needs to be verified. Using longitudinal recordings of frontal neurophysiological markers over many months during progressive dopaminergic lesion in non-human primates, we provide data that fail to support a simple interaction between dopamine, frontal function, and cognition. Feedback potentials, which are performance-monitoring signals sometimes thought to drive successful control, ceased to differentiate feedback valence at the end of the lesion, just before clinical motor threshold. In contrast, cognitive control performance and beta oscillatory markers of cognitive control were unimpaired by the lesion. The differing dynamics of these measures throughout a dopamine lesion suggests they are not all driven by dopamine in the same way. These dynamics also demonstrate that a complex non-linear set of mechanisms is engaged in the brain in response to a progressive dopamine lesion. These results question the direct causal chain from dopamine to frontal physiology and on to cognition. They imply that biomarkers of cognitive functions are not directly predictive of dopamine loss.
The ability to change behavioural strategies in the face of a changing world has been linked to the integrity of medial prefrontal cortex (mPFC) function in several species. While recording studies have found that mPFC representations reflect the strategy being used, lesion studies suggest that mPFC is necessary for changing strategy. Here we examine the relationship between representational changes in mPFC and behavioural strategy changes in the rat. We found that on tasks with a forced change in reward criterion, strategy-related representational transitions in mPFC occurred after animals learned that the reward contingency had changed, but before their behaviour changed. On tasks in which animals made their own strategic decisions, representational transitions in mPFC preceded changes in behaviour. These results suggest that mPFC does not merely reflect the action-selection policy of the animal, but rather that mPFC processes information related to a need for a change in strategy.
Unlabelled:
In humans, cognitively demanding tasks of many types recruit common frontoparietal brain areas. Pervasive activation of this "multiple-demand" (MD) network suggests a core function in supporting goal-oriented behavior. A similar network might therefore be predicted in nonhuman primates that readily perform similar tasks after training. However, an MD network in nonhuman primates has not been described. Single-cell recordings from macaque frontal and parietal cortex show some similar properties to human MD fMRI responses (e.g., adaptive coding of task-relevant information). Invasive recordings, however, come from limited prespecified locations, so they do not delineate a macaque homolog of the MD system and their positioning could benefit from knowledge of where MD foci lie. Challenges of scanning behaving animals mean that few macaque fMRI studies specifically contrast levels of cognitive demand, so we sought to identify a macaque counterpart to the human MD system using fMRI connectivity in 35 rhesus macaques. Putative macaque MD regions, mapped from frontoparietal MD regions defined in humans, were found to be functionally connected under anesthesia. To further refine these regions, an iterative process was used to maximize their connectivity cross-validated across animals. Finally, whole-brain connectivity analyses identified voxels that were robustly connected to MD regions, revealing seven clusters across frontoparietal and insular cortex comparable to human MD regions and one unexpected cluster in the lateral fissure. The proposed macaque MD regions can be used to guide future electrophysiological investigation of MD neural coding and in task-based fMRI to test predictions of similar functional properties to human MD cortex.
Significance statement:
In humans, a frontoparietal "multiple-demand" (MD) brain network is recruited during a wide range of cognitively demanding tasks. Because this suggests a fundamental function, one might expect a similar network to exist in nonhuman primates, but this remains controversial. Here, we sought to identify a macaque counterpart to the human MD system using fMRI connectivity. Putative macaque MD regions were functionally connected under anesthesia and were further refined by iterative optimization. The result is a network including lateral frontal, dorsomedial frontal, and insular and inferior parietal regions closely similar to the human counterpart. The proposed macaque MD regions can be useful in guiding electrophysiological recordings or in task-based fMRI to test predictions of similar functional properties to human MD cortex.
Significance
How does the “mind” (brain) influence the “body” (internal organs)? We identified key areas in the primate cerebral cortex that are linked through multisynaptic connections to the adrenal medulla. The most substantial influence originates from a broad network of motor areas that are involved in all aspects of skeletomotor control from response selection to motor preparation and movement execution. A smaller influence originates from a network in medial prefrontal cortex that is involved in the regulation of cognition and emotion. Thus, cortical areas involved in the control of movement, cognition, and affect are potential sources of central commands to influence sympathetic arousal. These results provide an anatomical basis for psychosomatic illness where mental states can alter organ function.
Curiosity and information seeking potently shapes our behaviour and are thought to rely on the frontal cortex. Yet, the frontal regions and neural dynamics that control the drive to check for information remain unknown. Here we trained monkeys in a task where they had the opportunity to gain information about the potential delivery of a large bonus reward or continue with a default instructed decision task. Single-unit recordings in behaving monkeys reveal that decisions to check for additional information first engage midcingulate cortex and then lateral prefrontal cortex. The opposite is true for instructed decisions. Importantly, deciding to check engages neurons also involved in performance monitoring. Further, specific midcingulate activity could be discerned several trials before the monkeys actually choose to check the environment. Our data show that deciding to seek information on the current state of the environment is characterized by specific dynamics of neural activity within the prefrontal cortex.
Primates display a remarkable ability to adapt to novel situations. Determining what is most pertinent in these situations is not always possible based only on the current sensory inputs, and often also depends on recent inputs and behavioral outputs that contribute to internal states. Thus, one can ask how cortical dynamics generate representations of these complex situations. It has been observed that mixed selectivity in cortical neurons contributes to represent diverse situations defined by a combination of the current stimuli, and that mixed selectivity is readily obtained in randomly connected recurrent networks. In this context, these reservoir networks reproduce the highly recurrent nature of local cortical connectivity. Recombining present and past inputs, random recurrent networks from the reservoir computing framework generate mixed selectivity which provides pre-coded representations of an essentially universal set of contexts. These representations can then be selectively amplified through learning to solve the task at hand. We thus explored their representational power and dynamical properties after training a reservoir to perform a complex cognitive task initially developed for monkeys. The reservoir model inherently displayed a dynamic form of mixed selectivity, key to the representation of the behavioral context over time. The pre-coded representation of context was amplified by training a feedback neuron to explicitly represent this context, thereby reproducing the effect of learning and allowing the model to perform more robustly. This second version of the model demonstrates how a hybrid dynamical regime combining spatio-temporal processing of reservoirs, and input driven attracting dynamics generated by the feedback neuron, can be used to solve a complex cognitive task. We compared reservoir activity to neural activity of dorsal anterior cingulate cortex of monkeys which revealed similar network dynamics. We argue that reservoir computing is a pertinent framework to model local cortical dynamics and their contribution to higher cognitive function.
Activity in anterior cingulate cortex (ACC) has been linked both to commitment to a course of action, even when it is associated with costs, and to exploring or searching for alternative courses of action. Here we review evidence that this is due to the presence of multiple signals in ACC reflecting the updating of beliefs and internal models of the environment and encoding aspects of choice value, including the average value of choices afforded by the environment (‘search value’). We contrast this evidence with the influential view that ACC activity is better described as reflecting task difficulty. A consideration of cortical neural network properties explains why ACC may carry such signals and also exhibit sensitivity to task difficulty.
Specialization and hierarchy are organizing principles for primate cortex, yet there is little direct evidence for how cortical areas are specialized in the temporal domain. We measured timescales of intrinsic fluctuations in spiking activity across areas and found a hierarchical ordering, with sensory and prefrontal areas exhibiting shorter and longer timescales, respectively. On the basis of our findings, we suggest that intrinsic timescales reflect areal specialization for task-relevant computations over multiple temporal ranges.
The ability to adjust one's behavioral strategy in complex environments is at the core of cognition. Doing so efficiently requires monitoring the reliability of the ongoing strategy and, when appropriate, switching away from it to evaluate alternatives. Studies in humans and non-human primates have uncovered signals in the anterior cingulate cortex (ACC) that reflect the pressure to switch away from the ongoing strategy, whereas other ACC signals relate to the pursuit of alternatives. However, whether these signals underlie computations that actually underpin strategy switching or merely reflect tracking of related variables remains unclear. Here we provide causal evidence that the rodent ACC actively arbitrates between persisting with the ongoing behavioral strategy and temporarily switching away to re-evaluate alternatives. Furthermore, by individually perturbing distinct output pathways, we establish that the two associated computations-determining whether to switch strategy and committing to the pursuit of a specific alternative-are segregated in the ACC microcircuitry.
Significance
The question of the whether rodent and primate medial frontal cortex (MFC) share similar functional organization, and whether the rodent medial frontal cortex is functionally analogous to the primate lateral prefrontal cortex (LPFC) is a contentious issue. Here, we probe this long-standing question by comparing whole-brain functional connectivity of the MFC in rodents, nonhuman primates (marmosets), and humans. The results demonstrated a remarkably similar intrinsic functional organization of the MFC across the three species, but clear differences between rodent and primate MFC whole-brain connectivity. Furthermore, in contrast to the common proposal that the rat MFC is functionally analogous with the primate LFC, our results demonstrate clear differences between the rodent MFC and primate LFC interareal functional connectivity.
With advances in connectomics, transcriptome and neurophysiological technologies, the neuroscience of brain-wide neural circuits is poised to take off. A major challenge is to understand how a vast diversity of functions is subserved by parcellated areas of mammalian neocortex composed of repetitions of a canonical local circuit. Areas of the cerebral cortex differ from each other not only in their input–output patterns but also in their biological properties. Recent experimental and theoretical work has revealed that such variations are not random heterogeneities; rather, synaptic excitation and inhibition display systematic macroscopic gradients across the entire cortex, and they are abnormal in mental illness. Quantitative differences along these gradients can lead to qualitatively novel behaviours in non-linear neural dynamical systems, by virtue of a phenomenon mathematically described as bifurcation. The combination of macroscopic gradients and bifurcations, in tandem with biological evolution, development and plasticity, provides a generative mechanism for functional diversity among cortical areas, as a general principle of large-scale cortical organization.
The midcingulate cortex (MCC) is viewed as a central node within a large-scale system devoted to adjusting behavior in the face of changing environments. Whereas the role of the MCC in interfacing action and cognition is well established, its role in regulating the autonomic nervous system is poorly understood. Yet, adaptive reactions to novel or threatening situations induce coordinated changes in the sympathetic and the parasympathetic systems. The somatomotor maps in the MCC are organized dorsoventrally. A meta-analysis of the literature reveals that the dorsoventral organization might also concern connections with the autonomic nervous system. Activation of the dorsal and ventral parts of the MCC correlate with recruitments of the sympathetic and the parasympathetic systems, respectively. Data also suggest that, in the MCC, projections toward the sympathetic system are mapped along the sensory-motor system following the same cervico-sacral organization as projections on the spinal cord for skeletal motor control.
Metastable brain dynamics are characterized by abrupt, jump-like modulations so that the neural activity in single trials appears to unfold as a sequence of discrete, quasi-stationary 'states'. Evidence that cortical neural activity unfolds as a sequence of metastable states is accumulating at fast pace. Metastable activity occurs both in response to an external stimulus and during ongoing, self-generated activity. These spontaneous metastable states are increasingly found to subserve internal representations that are not locked to external triggers, including states of deliberations, attention and expectation. Moreover, decoding stimuli or decisions via metastable states can be carried out trial-by-trial. Focusing on metastability will allow us to shift our perspective on neural coding from traditional concepts based on trial-averaging to models based on dynamic ensemble representations. Recent theoretical work has started to characterize the mechanistic origin and potential roles of metastable representations. In this article we review recent findings on metastable activity, how it may arise in biologically realistic models, and its potential role for representing internal states as well as relevant task variables.
Working memory is the fundamental function by which we break free from reflexive input-output reactions to gain control over our own thoughts. It has two types of mechanisms: online maintenance of information and its volitional or executive control. Classic models proposed persistent spiking for maintenance but have not explicitly addressed executive control. We review recent theoretical and empirical studies that suggest updates and additions to the classic model. Synaptic weight changes between sparse bursts of spiking strengthen working memory maintenance. Executive control acts via interplay between network oscillations in gamma (30–100 Hz) in superficial cortical layers (layers 2 and 3) and alpha and beta (10–30 Hz) in deep cortical layers (layers 5 and 6). Deep-layer alpha and beta are associated with top-down information and inhibition. It regulates the flow of bottom-up sensory information associated with superficial layer gamma. We propose that interactions between different rhythms in distinct cortical layers underlie working memory maintenance and its volitional control. Miller et al. present a new model of working memory. Synaptic weight changes between sparse spiking help strengthen working memory maintenance. Interplay between alpha, beta, and gamma rhythms in different cortical layers provide an infrastructure for its volitional control.
The function of the anterior cingulate cortex (ACC) remains controversial, yet many theories suggest a role in behavioral adaptation, partly because a robust event-related potential, the feedback-related negativity (FN), is evoked over the ACC whenever expectations are violated. We recorded from the ACC as rats performed a task identical to one that reliably evokes an FN in humans. A subset of neurons was found that encoded expected outcomes as abstract outcome representations. The degree to which a reward/non-reward outcome representation emerged during a trial depended on the history of outcomes that preceded it. A prediction error was generated on incongruent trials as the ensembles shifted from representing the expected to the actual outcome, at the same time point we have previously reported an FN in the local field potential. The results describe a novel mode of prediction error signaling by ACC neurons that is associated with the generation of an FN.
The selection and timing of actions are subject to determinate influences such as sensory cues and internal state as well as to effectively stochastic variability. Although stochastic choice mechanisms are assumed by many theoretical models, their origin and mechanisms remain poorly understood. Here we investigated this issue by studying how neural circuits in the frontal cortex determine action timing in rats performing a waiting task. Electrophysiological recordings from two regions necessary for this behavior, medial prefrontal cortex (mPFC) and secondary motor cortex (M2), revealed an unexpected functional dissociation. Both areas encoded deterministic biases in action timing, but only M2 neurons reflected stochastic trial-by-trial fluctuations. This differential coding was reflected in distinct timescales of neural dynamics in the two frontal cortical areas. These results suggest a two-stage model in which stochastic components of action timing decisions are injected by circuits downstream of those carrying deterministic bias signals.
Neocortical activity is permeated with endogenously generated fluctuations, but how these dynamics affect goal-directed behavior remains a mystery. We found that ensemble neural activity in primate visual cortex spontaneously fluctuated between phases of vigorous (On) and faint (Off) spiking synchronously across cortical layers. These On-Off dynamics, reflecting global changes in cortical state, were also modulated at a local scale during selective attention. Moreover, the momentary phase of local ensemble activity predicted behavioral performance. Our results show that cortical state is controlled locally within a cortical map according to cognitive demands and reveal the impact of these local changes in cortical state on goal-directed behavior.
Dorsal anterior cingulate cortex (dACC) carries a wealth of value-related information necessary for regulating behavioral flexibility and persistence. It signals error and reward events informing decisions about switching or staying with current behavior. During decision-making, it encodes the average value of exploring alternative choices (search value), even after controlling for response selection difficulty, and during learning, it encodes the degree to which internal models of the environment and current task must be updated. dACC value signals are derived in part from the history of recent reward integrated simultaneously over multiple time scales, thereby enabling comparison of experience over the recent and extended past. Such ACC signals may instigate attentionally demanding and difficult processes such as behavioral change via interactions with prefrontal cortex. However, the signal in dACC that instigates behavioral change need not itself be a conflict or difficulty signal.
Cortical networks are composed of glutamatergic excitatory projection neurons and local GABAergic inhibitory interneurons that gate signal flow and sculpt network dynamics. Although they represent a minority of the total neocortical neuronal population, GABAergic interneurons are highly heterogeneous, forming functional classes based on their morphological, electrophysiological, and molecular features, as well as connectivity and in vivo patterns of activity. Here we review our current understanding of neocortical interneuron diversity and the properties that distinguish cell types. We then discuss how the involvement of multiple cell types, each with a specific set of cellular properties, plays a crucial role in diversifying and increasing the computational power of a relatively small number of simple circuit motifs forming cortical networks. We illustrate how recent advances in the field have shed light onto the mechanisms by which GABAergic inhibition contributes to network operations.
When making a subjective choice, the brain must compute a value for each option and compare those values to make a decision. The orbitofrontal cortex (OFC) is critically involved in this process, but the neural mechanisms remain obscure, in part due to limitations in our ability to measure and control the internal deliberations that can alter the dynamics of the decision process. Here we tracked these dynamics by recovering temporally precise neural states from multidimensional data in OFC. During individual choices, OFC alternated between states associated with the value of two available options, with dynamics that predicted whether a subject would decide quickly or vacillate between the two alternatives. Ensembles of value-encoding neurons contributed to these states, with individual neurons shifting activity patterns as the network evaluated each option. Thus, the mechanism of subjective decision-making involves the dynamic activation of OFC states associated with each choice alternative.
Midcingulate cortex (MCC) has risen in prominence as human imaging identifies unique structural and functional activity therein and this is the first review of its structure, connections, functions and disease vulnerabilities. The MCC has two divisions (anterior, aMCC and posterior, pMCC) that represent functional units and the cytoarchitecture, connections and neurocytology of each is shown with immunohistochemistry and receptor binding. The MCC is not a division of anterior cingulate cortex (ACC) and the “dorsal ACC” designation is a misnomer as it incorrectly implies that MCC is a division of ACC. Interpretation of findings among species and developing models of human diseases requires detailed comparative studies which is shown here for five species with flat maps and immunohistochemistry (human, monkey, rabbit, rat, mouse). The largest neurons in human cingulate cortex are in layer Vb of area 24d in pMCC which project to the spinal cord. This area is part of the caudal cingulate premotor area which is involved in multisensory orientation of the head and body in space and neuron responses are tuned for the force and direction of movement. In contrast, the rostral cingulate premotor area in aMCC is involved in action-reinforcement associations and selection based on the amount of reward or aversive properties of a potential movement. The aMCC is activated by nociceptive information from the midline, mediodorsal and intralaminar thalamic nuclei which evoke fear and mediates nocifensive behaviors. This subregion also has high dopaminergic afferents and high dopamine-1 receptor binding and is engaged in reward processes. Opposing pain/avoidance and reward/approach functions are selected by assessment of potential outcomes and error detection according to feedback-mediated, decision making. Parietal afferents differentially terminate in MCC and provide for multisensory control in an eye- and head-centric manner. Finally, MCC vulnerability in human disease confirms the unique organization of MCC and supports the predictive validity of the MCC dichotomy. Vulnerability of aMCC is shown in chronic pain, obsessive-compulsive disorder with checking symptoms and attention-deficit/hyperactivity disorder and methylphenidate and pain medications selectively impact aMCC. In contrast, pMCC vulnerabilities are for progressive supranuclear palsy, unipolar depression and posttraumatic stress disorder. Thus, there is an emerging picture of the organization, functions and diseases of MCC. Future work will take this type of modular analysis to individual areas of which there are at least 10 in MCC.
Understanding the neural mechanisms of control regulation requires delineating specific functional roles for individual neural structures, and consequently their functional relationships. Higher-order control over behavior has traditionally been seen as the function of the prefrontal cortex (PFC). Models of various aspects of control, including top-down processing, decision making, and performance monitoring focus primarily on two subdivisions of the PFC, namely, the dorsolateral prefrontal cortex (DLPFC) and the medial frontal cortex, particularly the anterior cingulate cortex (ACC). Within these frameworks, DLPFC is allocated a role in the maintenance of representations of goals and means to achieve them in order to bias processes that depend on posterior brain areas, while medial frontal areas, again especially ACC, participate in performance monitoring, action evaluation and detection of events that indicate the need for behavioral adaptation and action revaluation. Furthermore different hierarchical levels of cognitive control are thought to be supported by different prefrontal subdivisions.
Animals monitor the outcome of their choice and adjust subsequent choice behavior using the outcome information. Together with the anterior cingulate cortex (ACC), the lateral habenula (LHb) has recently attracted attention for its crucial role in monitoring negative outcome. To investigate their contributions to subsequent behavioral adjustment, we recorded single-unit activity from the LHb and ACC in monkeys performing a reversal learning task. The monkey was required to shift a previous choice to the alternative if the choice had been repeatedly unrewarded in past trials. We found that ACC neurons stored outcome information from several past trials, whereas LHb neurons detected the ongoing negative outcome with shorter latencies. ACC neurons, but not LHb neurons, signaled a behavioral shift in the next trial. Our findings suggest that, although both the LHb and the ACC represent signals associated with negative outcome, these structures contribute to subsequent behavioral adjustment in different ways.
We developed a large-scale dynamical model of the macaque neocortex, which is based on recently acquired directed- and weighted-connectivity data from tract-tracing experiments, and which incorporates heterogeneity across areas. A hierarchy of timescales naturally emerges from this system: sensory areas show brief, transient responses to input (appropriate for sensory processing), whereas association areas integrate inputs over time and exhibit persistent activity (suitable for decision-making and working memory). The model displays multiple temporal hierarchies, as evidenced by contrasting responses to visual versus somatosensory stimulation. Moreover, slower prefrontal and temporal areas have a disproportionate impact on global brain dynamics. These findings establish a circuit mechanism for "temporal receptive windows" that are progressively enlarged along the cortical hierarchy, suggest an extension of time integration in decision making from local to large circuits, and should prompt a re-evaluation of the analysis of functional connectivity (measured by fMRI or electroencephalography/magnetoencephalography) by taking into account inter-areal heterogeneity.