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Cognitive control resolves conflict between task-relevant and -irrelevant information to enable goal-directed behavior. As conflict can arise from different sources (e.g., sensory input, internal representations), how a finite set of cognitive control processes can effectively address huge array of conflict remains a major challenge. We hypothesize that different conflict can be parameterized and represented as distinct points in a (low-dimensional) cognitive space, which can then be resolved by a limited set of cognitive control processes working along the dimensions. To test this hypothesis, we designed a task with five types of conflict that could be conceptually parameterized along one dimension. Over two experiments, both human performance and fMRI activity patterns in the right dorsolateral prefrontal (dlPFC) support that different types of conflict are organized in a cognitive space. The findings suggest that cognitive space can be a dimension reduction tool to effectively organize neural representations of conflict for cognitive control.

Flexibly controlling behavior to achieve a desired goal depends on the ability to monitor one’s own performance. A key open question is how performance monitoring can be both flexible to support multiple tasks and specialized to support specific tasks. We characterized performance monitoring representations by recording single neurons in the human medial frontal cortex (MFC). Subjects performed two tasks that involve three types of cognitive conflict. Neurons encoding error, conflict and predicted control demand in one or both tasks coexisted in the same population. Collectively, they gave rise to a representational geometry that simultaneously allowed task specialization and generalization. Representations of conflicts were compositional. Neurons encoding conflict retrospectively served to update estimates of control demand as predicted by a Bayesian model. These findings reveal how the MFC representation of evaluative signals are both abstract and specific, suggesting a mechanism for computing and maintaining control demand estimates across trials and tasks.

The effectiveness of rehabilitation treatment with the Body Weight Support (BWS) system has been demonstrated in patients with stroke and spinal cord injury. Many recent studies used expensive forc...

Controlling behavior to flexibly achieve desired goals depends on the ability to monitor one’s own performance. It is unknown how performance monitoring can be both flexible to support different tasks and specialized to perform well on each. We recorded single neurons in the human medial frontal cortex while subjects performed two tasks that involve three types of cognitive conflict. Neurons encoding predicted conflict, conflict, and error in one or both tasks were intermixed, forming a representational geometry that simultaneously allowed task specialization and generalization. Neurons encoding conflict retrospectively served to update internal estimates of control demand. Population representations of conflict were compositional. These findings reveal how representations of evaluative signals can be both abstract and task-specific and suggest a neuronal mechanism for estimating control demand.

This paper presents a tracking control method for pneumatic muscle actuators (PMAs). Considering that the PMA platform only feedbacks position, and the velocity and disturbances cannot be observed directly, we use the extended-state-observer (ESO) for simultaneously estimating the system states and disturbances by using measurable variables. Integrated with the ESO, a super twisting controller (STC) is design based on estimated states to realize the high-precision tracking. According to the Lyapunov theorem, the stability of the closed-loop system is ensured. Simulation and experimental studies are conducted, and the results show the convergence of the ESO and the effectiveness of the proposed method.

P systems are distributed and parallel computing models inspired from living cells. In this work, a variant of spiking neural P systems, cortical neural P systems, are proposed in the frame work of P systems combining the topology structure of basic P system and information processing style in spiking neurons. The computational power of cortical neural P systems is investigated. It is proved that cortical neural P systems are equivalent to Turing machines as number generators.

A recent single-neuron study revealed an anatomical anterior-to-posterior gradient of awareness-related responses by 'concept neurons' in the human medial temporal lobe (MTL). Delayed and weaker responses were indicative of the failure of a stimulus to reach awareness, suggesting that reliable fast responses are a critical aspect of the neural mechanisms of consciousness.

People often make decisions in the face of ambiguous information, but it remains unclear how ambiguity is represented in the brain. We used three types of ambiguous stimuli and combined EEG and fMRI to examine the neural representation of perceptual decisions under ambiguity. We identified a late positive potential, the LPP, which differentiated levels of ambiguity, and which was specifically associated with behavioral judgments about choices that were ambiguous, rather than passive perception of ambiguous stimuli. Mediation analyses together with two further control experiments confirmed that the LPP was generated only when decisions are made (not during mere perception of ambiguous stimuli), and only when those decisions involved choices on a dimension that is ambiguous. A further control experiment showed that a stronger LPP arose in the presence of ambiguous stimuli compared to when only unambiguous stimuli were present. Source modeling suggested that the LPP originated from multiple loci in cingulate cortex, a finding we further confirmed using fMRI and fMRI-guided ERP source prediction. Taken together, our findings argue for a role of an LPP originating from cingulate cortex in encoding decisions based on task-relevant perceptual ambiguity, a process that may in turn influence confidence judgment, response conflict, and error correction.

Humans can self-monitor errors without explicit feedback, resulting in behavioral adjustments on subsequent trials such as post-error slowing (PES). The error-related negativity (ERN) is a well-established macroscopic scalp EEG correlate of error self-monitoring, but its neural origins and relationship to PES remain unknown. We recorded in the frontal cortex of patients performing a Stroop task and found neurons that track self-monitored errors and error history in dorsal anterior cingulate cortex (dACC) and pre-supplementary motor area (pre-SMA). Both the intracranial ERN (iERN) and error neuron responses appeared first in pre-SMA, and ~50 ms later in dACC. Error neuron responses were correlated with iERN amplitude on individual trials. In dACC, such error neuron-iERN synchrony and responses of error-history neurons predicted the magnitude of PES. These data reveal a human single-neuron correlate of the ERN and suggest that dACC synthesizes error information to recruit behavioral control through coordinated neural activity.

SummaryBroadly neutralizing antibodies (bNAbs) to HIV-1 can prevent infection and are therefore of great importance for HIV-1 vaccine design. Notably, bNAbs are highly somatically mutated and generated by a fraction of HIV-1-infected individuals several years after infection. Antibodies typically accumulate mutations in the complementarity determining region (CDR) loops, which usually contact the antigen. The CDR loops are scaffolded by canonical framework regions (FWRs) that are both resistant to and less tolerant of mutations. Here, we report that in contrast to most antibodies, including those with limited HIV-1 neutralizing activity, most bNAbs require somatic mutations in their FWRs. Structural and functional analyses reveal that somatic mutations in FWR residues enhance breadth and potency by providing increased flexibility and/or direct antigen contact. Thus, in bNAbs, FWRs play an essential role beyond scaffolding the CDR loops and their unusual contribution to potency and breadth should be considered in HIV-1 vaccine design.