M1-selective muscarinic allosteric modulation enhances cognitive flexibility and effective salience in nonhuman primates.

Acetylcholine (ACh) in cortical neural circuits mediates how selective attention is sustained in the presence of distractors and how flexible cognition adjusts to changing task demands. The cognitive domains of attention and cognitive flexibility might be differentially supported by the M1 muscarinic acetylcholine receptor (mAChR) subtype. Understanding how M1 mAChR mechanisms support these cognitive subdomains is of highest importance for advancing novel drug treatments for conditions with altered attention and reduced cognitive control including Alzheimer's disease or schizophrenia. Here, we tested this question by assessing how the subtype-selective M1 mAChR positive allosteric modulator (PAM) VU0453595 affects visual search and flexible reward learning in nonhuman primates. We found that allosteric potentiation of M1 mAChRs enhanced flexible learning performance by improving extradimensional set shifting, reducing latent inhibition from previously experienced distractors and reducing response perseveration in the absence of adverse side effects. These procognitive effects occurred in the absence of apparent changes of attentional performance during visual search. In contrast, nonselective ACh modulation using the acetylcholinesterase inhibitor (AChEI) donepezil improved attention during visual search at doses that did not alter cognitive flexibility and that already triggered gastrointestinal cholinergic side effects. These findings illustrate that M1 mAChR positive allosteric modulation enhances cognitive flexibility without affecting attentional filtering of distraction, consistent with M1 activity boosting the effective salience of relevant over irrelevant objects specifically during learning. These results suggest that M1 PAMs are versatile compounds for enhancing cognitive flexibility in disorders spanning schizophrenia and Alzheimer's diseases.

Anterior cingulate cortex causally supports flexible learning under motivationally challenging and cognitively demanding conditions.

Anterior cingulate cortex (ACC) and striatum (STR) contain neurons encoding not only the expected values of actions, but also the value of stimulus features irrespective of actions. Values about stimulus features in ACC or STR might contribute to adaptive behavior by guiding fixational information sampling and biasing choices toward relevant objects, but they might also have indirect motivational functions by enabling subjects to estimate the value of putting effort into choosing objects. Here, we tested these possibilities by modulating neuronal activity in ACC and STR of nonhuman primates using transcranial ultrasound stimulation while subjects learned the relevance of objects in situations with varying motivational and cognitive demands. Motivational demand was indexed by varying gains and losses during learning, while cognitive demand was varied by increasing the uncertainty about which object features could be relevant during learning. We found that ultrasound stimulation of the ACC, but not the STR, reduced learning efficiency and prolonged information sampling when the task required averting losses and motivational demands were high. Reduced learning efficiency was particularly evident at higher cognitive demands and when subjects experienced loss of already attained tokens. These results suggest that the ACC supports flexible learning of feature values when loss experiences impose a motivational challenge and when uncertainty about the relevance of objects is high. Taken together, these findings provide causal evidence that the ACC facilitates resource allocation and improves visual information sampling during adaptive behavior.

Fast spiking interneuron activity in primate striatum tracks learning of attention cues.

Cognitive flexibility depends on a fast neural learning mechanism for enhancing momentary relevant over irrelevant information. A possible neural mechanism realizing this enhancement uses fast spiking interneurons (FSIs) in the striatum to train striatal projection neurons to gate relevant and suppress distracting cortical inputs. We found support for such a mechanism in nonhuman primates during the flexible adjustment of visual attention in a reversal learning task. FSI activity was modulated by visual attention cues during feature-based learning. One FSI subpopulation showed stronger activation during learning, while another FSI subpopulation showed response suppression after learning, which could indicate a disinhibitory effect on the local circuit. Additionally, FSIs that showed response suppression to learned attention cues were activated by salient distractor events, suggesting they contribute to suppressing bottom-up distraction. These findings suggest that striatal fast spiking interneurons play an important role when cues are learned that redirect attention away from previously relevant to newly relevant visual information. This cue-specific activity was independent of motor-related activity and thus tracked specifically the learning of reward predictive visual features.

Gains and Losses Affect Learning Differentially at Low and High Attentional Load.

Prospective gains and losses influence cognitive processing, but it is unresolved how they modulate flexible learning in changing environments. The prospect of gains might enhance flexible learning through prioritized processing of reward-predicting stimuli, but it is unclear how far this learning benefit extends when task demands increase. Similarly, experiencing losses might facilitate learning when they trigger attentional reorienting away from loss-inducing stimuli, but losses may also impair learning by increasing motivational costs or when negative outcomes are overgeneralized. To clarify these divergent views, we tested how varying magnitudes of gains and losses affect the flexible learning of feature values in environments that varied attentional load by increasing the number of interfering object features. With this task design, we found that larger prospective gains improved learning efficacy and learning speed, but only when attentional load was low. In contrast, expecting losses impaired learning efficacy, and this impairment was larger at higher attentional load. These findings functionally dissociate the contributions of gains and losses on flexible learning, suggesting they operate via separate control mechanisms. One mechanism is triggered by experiencing loss and reduces the ability to reduce distractor interference, impairs assigning credit to specific loss-inducing features, and decreases efficient exploration during learning. The second mechanism is triggered by experiencing gains, which enhances prioritizing reward-predicting stimulus features as long as the interference of distracting features is limited. Taken together, these results support a rational theory of cognitive control during learning, suggesting that experiencing losses and experiencing distractor interference impose costs for learning.

Learning at Variable Attentional Load Requires Cooperation of Working Memory, Meta-learning, and Attention-augmented Reinforcement Learning.

Flexible learning of changing reward contingencies can be realized with different strategies. A fast learning strategy involves using working memory of recently rewarded objects to guide choices. A slower learning strategy uses prediction errors to gradually update value expectations to improve choices. How the fast and slow strategies work together in scenarios with real-world stimulus complexity is not well known. Here, we aim to disentangle their relative contributions in rhesus monkeys while they learned the relevance of object features at variable attentional load. We found that learning behavior across six monkeys is consistently best predicted with a model combining (i) fast working memory and (ii) slower reinforcement learning from differently weighted positive and negative prediction errors as well as (iii) selective suppression of nonchosen feature values and (iv) a meta-learning mechanism that enhances exploration rates based on a memory trace of recent errors. The optimal model parameter settings suggest that these mechanisms cooperate differently at low and high attentional loads. Whereas working memory was essential for efficient learning at lower attentional loads, enhanced weighting of negative prediction errors and meta-learning were essential for efficient learning at higher attentional loads. Together, these findings pinpoint a canonical set of learning mechanisms and suggest how they may cooperate when subjects flexibly adjust to environments with variable real-world attentional demands.

Multineuromodulator measurements across fronto-striatal network areas of the behaving macaque using solid-phase microextraction.

Different neuromodulators rarely act independent from each other to modify neural processes but are instead coreleased, gated, or modulated. To understand this interdependence of neuromodulators and their collective influence on local circuits during different brain states, it is necessary to reliably extract local concentrations of multiple neuromodulators in vivo. Here we describe results using solid-phase microextraction (SPME), a method providing sensitive, multineuromodulator measurements. SPME is a sampling method that is coupled with mass spectrometry to quantify collected analytes. Reliable measurements of glutamate, dopamine, acetylcholine, and choline were made simultaneously within frontal cortex and striatum of two macaque monkeys (Macaca mulatta) during goal-directed behavior. We find glutamate concentrations several orders of magnitude higher than acetylcholine and dopamine in all brain regions. Dopamine was reliably detected in the striatum at tenfold higher concentrations than acetylcholine. Acetylcholine and choline concentrations were detected with high consistency across brain areas within monkeys and between monkeys. These findings illustrate that SPME microprobes provide a versatile novel tool to characterize multiple neuromodulators across different brain areas in vivo to understand the interdependence and covariation of neuromodulators during goal-directed behavior. Such data would be important to better distinguish between different behavioral states and characterize dysfunctional brain states that may be evident in psychiatric disorders.NEW & NOTEWORTHY Our paper reports a reliable and sensitive novel method for measuring the absolute concentrations of glutamate, acetylcholine, choline, dopamine, and serotonin in brain circuits in vivo. We show that this method reliably samples multiple neurochemicals in three brain areas simultaneously while nonhuman primates are engaged in goal-directed behavior. We further describe how the methodology we describe here may be used by electrophysiologists as a low-barrier-to-entry tool for measuring multiple neurochemicals.

Solid Phase Microextraction-Based Miniaturized Probe and Protocol for Extraction of Neurotransmitters from Brains in Vivo.

Despite the importance of monitoring and correlating neurotransmitter concentrations in the brain with observable behavior and brain areas in which they act, in vivo measurement of multiple neurochemicals in the brain remains a challenge. Here, we propose an alternative solid phase microextraction-based (SPME) chemical biopsy approach as a viable method for acquirement of quantitative information on multiple neurotransmitters by one device within a single sampling event, with multisite measurement capabilities and minimized invasiveness, as no tissue is removed. The miniaturized SPME probe developed for integrated in vivo sampling/sample preparation has been thoroughly optimized with respect to probe shape, desorption solvent, and extracting phase tailored for extraction of small hydrophilic molecules via synthesis and functionalization of the SPME coating. Experimental evaluations of sampling time and storage strategy led to achieving appropriate temporal resolution versus recovery balance as well as little or no analyte loss, respectively. Validation of the developed SPME-HPLC-MS/MS protocol in a surrogate brain matrix yielded satisfactory accuracies of 80-100%, precision below 17%, as well as linear dynamic range and limits of quantitation suitable for determining neurochemicals at physiologically relevant levels. Finally, we present a proof-of-concept in vivo application in macaque brain, where several target neurotransmitters were extracted simultaneously from three brain areas. The developed probe and protocol are herein presented as a potential powerful addition to the existing in vivo toolbox for measurements of local levels of neurochemicals in multiple brain systems implicated in the neuropathology of psychiatric disorders.

Stimulus-induced visual cortical networks are recapitulated by spontaneous local and interareal synchronization.

Intrinsic covariation of brain activity has been studied across many levels of brain organization. Between visual areas, neuronal activity covaries primarily among portions with similar retinotopic selectivity. We hypothesized that spontaneous interareal coactivation is subserved by neuronal synchronization. We performed simultaneous high-density electrocorticographic recordings across the dorsal aspect of several visual areas in one hemisphere in each of two awake monkeys to investigate spatial patterns of local and interareal synchronization. We show that stimulation-induced patterns of interareal coactivation were reactivated in the absence of stimulation for the visual quadrant covered. Reactivation occurred through both interareal cofluctuation of local activity and interareal phase synchronization. Furthermore, the trial-by-trial covariance of the induced responses recapitulated the pattern of interareal coupling observed during stimulation, i.e., the signal correlation. Reactivation-related synchronization showed distinct peaks in the theta, alpha, and gamma frequency bands. During passive states, this rhythmic reactivation was augmented by specific patterns of arrhythmic correspondence. These results suggest that networks of intrinsic covariation observed at multiple levels and with several recording techniques are related to synchronization and that behavioral state may affect the structure of intrinsic dynamics.

Quaddles: A multidimensional 3-D object set with parametrically controlled and customizable features.

Many studies of vision and cognition require novel three-dimensional object sets defined by a parametric feature space. Creating such sets and verifying that they are suitable for a given task, however, can be time-consuming and effortful. Here we present a new set of multidimensional objects, Quaddles, designed for studies of feature-based learning and attention, but adaptable for many research purposes. Quaddles have features that are all equally visible from any angle around the vertical axis and can be designed to be equally discriminable along feature dimensions; these objects do not show strong or consistent response biases, with a small number of quantified exceptions. They are available as two-dimensional images, rotating videos, and FBX object files suitable for use with any modern video game engine. We also provide scripts that can be used to generate hundreds of thousands of further Quaddles, as well as examples and tutorials for modifying Quaddles or creating completely new object sets from scratch, with the aim to speed up the development time of future novel-object studies.

Brief activation of GABAergic interneurons initiates the transition to ictal events through post-inhibitory rebound excitation.

Activation of γ-aminobutyric acid (GABAA) receptors have been associated with the onset of epileptiform events. To investigate if a causal relationship exists between GABAA receptor activation and ictal event onset, we activated inhibitory GABAergic networks in the superficial layer (2/3) of the somatosensory cortex during hyperexcitable conditions using optogenetic techniques in mice expressing channelrhodopsin-2 in all GABAergic interneurons. We found that a brief 30ms light pulse reliably triggered either an interictal-like event (IIE) or ictal-like ("ictal") event in the in vitro cortical 4-Aminopyridine (4-AP) slice model. The link between light pulse and epileptiform event onset was lost following blockade of GABAA receptors with bicuculline methiodide. Additionally, recording the chronological sequence of events following a light pulse in a variety of configurations (whole-cell, gramicidin-perforated patch, and multi-electrode array) demonstrated an initial hyperpolarization followed by post-inhibitory rebound spiking and a subsequent slow depolarization at the transition to epileptiform activity. Furthermore, the light-triggered ictal events were independent of the duration or intensity of the initiating light pulse, suggesting an underlying regenerative mechanism. Moreover, we demonstrated that brief GABAA receptor activation can initiate ictal events in the in vivo 4-AP mouse model, in another common in vitro model of epileptiform activity, and in neocortical tissue resected from epilepsy patients. Our findings reveal that the synchronous activation of GABAergic interneurons is a robust trigger for ictal event onset in hyperexcitable cortical networks.

Theta-gamma coordination between anterior cingulate and prefrontal cortex indexes correct attention shifts.

Anterior cingulate and lateral prefrontal cortex (ACC/PFC) are believed to coordinate activity to flexibly prioritize the processing of goal-relevant over irrelevant information. This between-area coordination may be realized by common low-frequency excitability changes synchronizing segregated high-frequency activations. We tested this coordination hypothesis by recording in macaque ACC/PFC during the covert utilization of attention cues. We found robust increases of 5-10 Hz (theta) to 35-55 Hz (gamma) phase-amplitude correlation between ACC and PFC during successful attention shifts but not before errors. Cortical sites providing theta phases (i) showed a prominent cue-induced phase reset, (ii) were more likely in ACC than PFC, and (iii) hosted neurons with burst firing events that synchronized to distant gamma activity. These findings suggest that interareal theta-gamma correlations could follow mechanistically from a cue-triggered reactivation of rule memory that synchronizes theta across ACC/PFC.

Ketamine Alters Outcome-Related Local Field Potentials in Monkey Prefrontal Cortex.

A subanesthetic dose of the noncompetitive N-methyl-d-aspartate receptor antagonist ketamine is known to induce a schizophrenia-like phenotype in humans and nonhuman primates alike. The transient behavioral changes mimic the positive, negative, and cognitive symptoms of the disease but the neural mechanisms behind these changes are poorly understood. A growing body of evidence indicates that the cognitive control processes associated with prefrontal cortex (PFC) regions relies on groups of neurons synchronizing at narrow-band frequencies measurable in the local field potential (LFP). Here, we recorded LFPs from the caudo-lateral PFC of 2 macaque monkeys performing an antisaccade task, which requires the suppression of an automatic saccade toward a stimulus and the initiation of a goal-directed saccade in the opposite direction. Preketamine injection activity showed significant differences in a narrow 20-30 Hz beta frequency band between correct and error trials in the postsaccade response epoch. Ketamine significantly impaired the animals' performance and was associated with a loss of the differences in outcome-specific beta-band power. Instead, we observed a large increase in high-gamma-band activity. Our results suggest that the PFC employs beta-band synchronization to prepare for top-down cognitive control of saccades and the monitoring of task outcome.

Interareal Spike-Train Correlations of Anterior Cingulate and Dorsal Prefrontal Cortex during Attention Shifts.

The anterior cingulate cortex (ACC) and prefrontal cortex (PFC) are believed to coactivate during goal-directed behavior to identify, select, and monitor relevant sensory information. Here, we tested whether coactivation of neurons across macaque ACC and PFC would be evident at the level of pairwise neuronal correlations during stimulus selection in a spatial attention task. We found that firing correlations emerged shortly after an attention cue, were evident for 50-200 ms time windows, were strongest for neuron pairs in area 24 (ACC) and areas 8 and 9 (dorsal PFC), and were independent of overall firing rate modulations. For a subset of cell pairs from ACC and dorsal PFC, the observed functional spike-train connectivity carried information about the direction of the attention shift. Reliable firing correlations were evident across area boundaries for neurons with broad spike waveforms (putative excitatory neurons) as well as for pairs of putative excitatory neurons and neurons with narrow spike waveforms (putative interneurons). These findings reveal that stimulus selection is accompanied by slow time scale firing correlations across those ACC/PFC subfields implicated to control and monitor attention. This functional coupling was informative about which stimulus was selected and thus indexed possibly the exchange of task-relevant information. We speculate that interareal, transient firing correlations reflect the transient coordination of larger, reciprocally interacting brain networks at a characteristic 50-200 ms time scale. Significance statement: Our manuscript identifies interareal spike-train correlations between primate anterior cingulate and dorsal prefrontal cortex during a period where attentional stimulus selection is likely controlled by these very same circuits. Interareal correlations emerged during the covert attention shift to one of two peripheral stimuli, proceeded on a slow 50-200 ms time scale, and occurred between putative pyramidal and putative interneurons. Spike-train correlations emerged particularly for cell pairs tuned to similar contralateral target locations, thus indexing the interareal coordination of attention-relevant information. These findings characterize a possible way by which prefrontal and anterior cingulate cortex circuits implement their control functions through coordinated firing when macaque monkeys select and monitor relevant stimuli for goal-directed behaviors.

Mapping of functionally characterized cell classes onto canonical circuit operations in primate prefrontal cortex.

Microcircuits are composed of multiple cell classes that likely serve unique circuit operations. But how cell classes map onto circuit functions is largely unknown, particularly for primate prefrontal cortex during actual goal-directed behavior. One difficulty in this quest is to reliably distinguish cell classes in extracellular recordings of action potentials. Here we surmount this issue and report that spike shape and neural firing variability provide reliable markers to segregate seven functional classes of prefrontal cells in macaques engaged in an attention task. We delineate an unbiased clustering protocol that identifies four broad spiking (BS) putative pyramidal cell classes and three narrow spiking (NS) putative inhibitory cell classes dissociated by how sparse, bursty, or regular they fire. We speculate that these functional classes map onto canonical circuit functions. First, two BS classes show sparse, bursty firing, and phase synchronize their spiking to 3-7 Hz (theta) and 12-20 Hz (beta) frequency bands of the local field potential (LFP). These properties make cells flexibly responsive to network activation at varying frequencies. Second, one NS and two BS cell classes show regular firing and higher rate with only marginal synchronization preference. These properties are akin to setting tonically the excitation and inhibition balance. Finally, two NS classes fired irregularly and synchronized to either theta or beta LFP fluctuations, tuning them potentially to frequency-specific subnetworks. These results suggest that a limited set of functional cell classes emerges in macaque prefrontal cortex (PFC) during attentional engagement to not only represent information, but to subserve basic circuit operations.

Sharp Wave Ripples during Visual Exploration in the Primate Hippocampus.

Hippocampal sharp-wave ripples (SWRs) are highly synchronous oscillatory field potentials that are thought to facilitate memory consolidation. SWRs typically occur during quiescent states, when neural activity reflecting recent experience is replayed. In rodents, SWRs also occur during brief locomotor pauses in maze exploration, where they appear to support learning during experience. In this study, we detected SWRs that occurred during quiescent states, but also during goal-directed visual exploration in nonhuman primates (Macaca mulatta). The exploratory SWRs showed peak frequency bands similar to those of quiescent SWRs, and both types were inhibited at the onset of their respective behavioral epochs. In apparent contrast to rodent SWRs, these exploratory SWRs occurred during active periods of exploration, e.g., while animals searched for a target object in a scene. SWRs were associated with smaller saccades and longer fixations. Also, when they coincided with target-object fixations during search, detection was more likely than when these events were decoupled. Although we observed high gamma-band field potentials of similar frequency to SWRs, only the SWRs accompanied greater spiking synchrony in neural populations. These results reveal that SWRs are not limited to off-line states as conventionally defined; rather, they occur during active and informative performance windows. The exploratory SWR in primates is an infrequent occurrence associated with active, attentive performance, which may indicate a new, extended role of SWRs during exploration in primates. SIGNIFICANCE STATEMENT: Sharp-wave ripples (SWRs) are high-frequency oscillations that generate highly synchronized activity in neural populations. Their prevalence in sleep and quiet wakefulness, and the memory deficits that result from their interruption, suggest that SWRs contribute to memory consolidation during rest. Here, we report that SWRs from the monkey hippocampus occur not only during behavioral inactivity but also during successful visual exploration. SWRs were associated with attentive, focal search and appeared to enhance perception of locations viewed around the time of their occurrence. SWRs occurring in rest are noteworthy for their relation to heightened neural population activity, temporally precise and widespread synchronization, and memory consolidation; therefore, the SWRs reported here may have a similar effect on neural populations, even as experiences unfold.

Attentional Selection Can Be Predicted by Reinforcement Learning of Task-relevant Stimulus Features Weighted by Value-independent Stickiness.

Attention includes processes that evaluate stimuli relevance, select the most relevant stimulus against less relevant stimuli, and bias choice behavior toward the selected information. It is not clear how these processes interact. Here, we captured these processes in a reinforcement learning framework applied to a feature-based attention task that required macaques to learn and update the value of stimulus features while ignoring nonrelevant sensory features, locations, and action plans. We found that value-based reinforcement learning mechanisms could account for feature-based attentional selection and choice behavior but required a value-independent stickiness selection process to explain selection errors while at asymptotic behavior. By comparing different reinforcement learning schemes, we found that trial-by-trial selections were best predicted by a model that only represents expected values for the task-relevant feature dimension, with nonrelevant stimulus features and action plans having only a marginal influence on covert selections. These findings show that attentional control subprocesses can be described by (1) the reinforcement learning of feature values within a restricted feature space that excludes irrelevant feature dimensions, (2) a stochastic selection process on feature-specific value representations, and (3) value-independent stickiness toward previous feature selections akin to perseveration in the motor domain. We speculate that these three mechanisms are implemented by distinct but interacting brain circuits and that the proposed formal account of feature-based stimulus selection will be important to understand how attentional subprocesses are implemented in primate brain networks.

Prefrontal and anterior cingulate cortex neurons encode attentional targets even when they do not apparently bias behavior.

Neurons in anterior cingulate and prefrontal cortex (ACC/PFC) carry information about behaviorally relevant target stimuli. This information is believed to affect behavior by exerting a top-down attentional bias on stimulus selection. However, attention information may not necessarily be a biasing signal but could be a corollary signal that is not directly related to ongoing behavioral success, or it could reflect the monitoring of targets similar to an eligibility trace useful for later attentional adjustment. To test this suggestion we quantified how attention information relates to behavioral success in neurons recorded in multiple subfields in macaque ACC/PFC during a cued attention task. We found that attention cues activated three separable neuronal groups that encoded spatial attention information but were differently linked to behavioral success. A first group encoded attention targets on correct and error trials. This group spread across ACC/PFC and represented targets transiently after cue onset, irrespective of behavior. A second group encoded attention targets on correct trials only, closely predicting behavior. These neurons were not only prevalent in lateral prefrontal but also in anterior cingulate cortex. A third group encoded target locations only on error trials. This group was evident in ACC and PFC and was activated in error trials "as if" attention was shifted to the target location but without evidence for such behavior. These results show that only a portion of neuronaly available information about attention targets biases behavior. We speculate that additionally a unique neural subnetwork encodes counterfactual attention information.

Dorsolateral Prefrontal Cortex Deactivation in Monkeys Reduces Preparatory Beta and Gamma Power in the Superior Colliculus.

Cognitive control requires the selection and maintenance of task-relevant stimulus-response associations, or rules. The dorsolateral prefrontal cortex (DLPFC) has been implicated by lesion, functional imaging, and neurophysiological studies to be involved in encoding rules, but the mechanisms by which it modulates other brain areas are poorly understood. Here, the functional relationship of the DLPFC with the superior colliculus (SC) was investigated by bilaterally deactivating the DLPFC while recording local field potentials (LFPs) in the SC in monkeys performing an interleaved pro- and antisaccade task. Event-related LFPs showed differences between pro- and antisaccades and responded prominently to stimulus presentation. LFP power after stimulus onset was higher for correct saccades than erroneous saccades. Deactivation of the DLPFC did not affect stimulus onset related LFP activity, but reduced high beta (20-30 Hz) and high gamma (60-150 Hz) power during the preparatory period for both pro- and antisaccades. Spike rate during the preparatory period was positively correlated with gamma power and this relationship was attenuated by DLPFC deactivation. These results suggest that top-down control of the SC by the DLPFC may be mediated by beta oscillations.

Anterior Cingulate Cortex Cells Identify Process-Specific Errors of Attentional Control Prior to Transient Prefrontal-Cingulate Inhibition.

Errors indicate the need to adjust attention for improved future performance. Detecting errors is thus a fundamental step to adjust and control attention. These functions have been associated with the dorsal anterior cingulate cortex (dACC), predicting that dACC cells should track the specific processing states giving rise to errors in order to identify which processing aspects need readjustment. Here, we tested this prediction by recording cells in the dACC and lateral prefrontal cortex (latPFC) of macaques performing an attention task that dissociated 3 processing stages. We found that, across prefrontal subareas, the dACC contained the largest cell populations encoding errors indicating (1) failures of inhibitory control of the attentional focus, (2) failures to prevent bottom-up distraction, and (3) lapses when implementing a choice. Error-locked firing in the dACC showed the earliest latencies across the PFC, emerged earlier than reward omission signals, and involved a significant proportion of putative inhibitory interneurons. Moreover, early onset error-locked response enhancement in the dACC was followed by transient prefrontal-cingulate inhibition, possibly reflecting active disengagement from task processing. These results suggest a functional specialization of the dACC to track and identify the actual processes that give rise to erroneous task outcomes, emphasizing its role to control attentional performance.

Visual cortical gamma-band activity during free viewing of natural images.

Gamma-band activity in visual cortex has been implicated in several cognitive operations, like perceptual grouping and attentional selection. So far, it has been studied primarily under well-controlled visual fixation conditions and using well-controlled stimuli, like isolated bars or patches of grating. If gamma-band activity is to subserve its purported functions outside of the laboratory, it should be present during natural viewing conditions. We recorded neuronal activity with a 252-channel electrocorticographic (ECoG) grid covering large parts of the left hemisphere of 2 macaque monkeys, while they freely viewed natural images. We found that natural viewing led to pronounced gamma-band activity in the visual cortex. In area V1, gamma-band activity during natural viewing showed a clear spectral peak indicative of oscillatory activity between 50 and 80 Hz and was highly significant for each of 65 natural images. Across the ECoG grid, gamma-band activity during natural viewing was present over most of the recorded visual cortex and absent over most remaining cortex. After saccades, the gamma peak frequency slid down to 30-40 Hz at around 80 ms postsaccade, after which the sustained 50- to 80-Hz gamma-band activity resumed. We propose that gamma-band activity plays an important role during natural viewing.