Working memory (WM) provides the stability necessary for high-level cognition. Influential theories typically assume that WM depends on the persistence of stable neural representations, yet increasing evidence suggests that neural states are highly dynamic. Here we apply multivariate pattern analysis to explore the population dynamics in primate lateral prefrontal cortex (PFC) during three variants of the classic memory-guided saccade task (recorded in four animals). We observed the hallmark of dynamic population coding across key phases of a working memory task: sensory processing, memory encoding, and response execution. Throughout both these dynamic epochs and the memory delay period, however, the neural representational geometry remained stable. We identified two characteristics that jointly explain these dynamics: (1) time-varying changes in the subpopulation of neurons coding for task variables (i.e., dynamic subpopulations); and (2) time-varying selectivity within neurons (i.e., dynamic selectivity). These results indicate that even in a very simple memory-guided saccade task, PFC neurons display complex dynamics to support stable representations for WM.SIGNIFICANCE STATEMENT Flexible, intelligent behavior requires the maintenance and manipulation of incoming information over various time spans. For short time spans, this faculty is labeled “working memory” (WM). Dominant models propose that WM is maintained by stable, persistent patterns of neural activity in prefrontal cortex (PFC). However, recent evidence suggests that neural activity in PFC is dynamic, even while the contents of WM remain stably represented. Here, we explored the neural dynamics in PFC during a memory-guided saccade task. We found evidence for dynamic population coding in various task epochs, despite striking stability in the neural representational geometry of WM. Furthermore, we identified two distinct cellular mechanisms that contribute to dynamic population coding.

Prolonged expression of the CRISPR-Cas9 nuclease and gRNA from viral vectors may cause off-target mutagenesis and immunogenicity. Thus, a transient delivery system is needed for therapeutic genome editing applications. Here, we develop an extracellular nanovesicle-based ribonucleoprotein delivery system named NanoMEDIC by utilizing two distinct homing mechanisms. Chemical induced dimerization recruits Cas9 protein into extracellular nanovesicles, and then a viral RNA packaging signal and two self-cleaving riboswitches tether and release sgRNA into nanovesicles. We demonstrate efficient genome editing in various hardto-transfect cell types, including human induced pluripotent stem (iPS) cells, neurons, and myoblasts. NanoMEDIC also achieves over 90% exon skipping efficiencies in skeletal muscle cells derived from Duchenne muscular dystrophy (DMD) patient iPS cells. Finally, single intramuscular injection of NanoMEDIC induces permanent genomic exon skipping in a luciferase reporter mouse and in mdx mice, indicating its utility for in vivo genome editing therapy of DMD and beyond.

Simultaneous performance of two tasks often leads to performance deficits in the component tasks. This effect, known as dual-task interference, is thought to be a proof of capacity limitation in cognition, and the lateral prefrontal cortex (LPFC) has been highlighted as its putative neural substrate. Here we recorded single-neuron activities in LPFC while monkeys performed dual tasks that required the simultaneous performance of a varying-load spatial attention task and a spatial memory task. We found that the performance of the monkeys exhibited dual-task interference, and prefrontal neuron activities showed a decreased ability to represent task-relevant information to a degree proportional to the increased demand of the concurrent counterpart task. The locus of the interference was shown to originate in the simultaneous, overloaded recruitment of the same LPFC neural population by the two tasks. These results provide direct neurophysiological evidence for, and constraints to, psychological models of dual-task interference and capacity limitation.

Electrocorticogram (ECoG) has great potential as a source signal, especially for clinical BMI. Until recently, ECoG electrodes were commonly used for identifying epileptogenic foci in clinical situations, and such electrodes were low-density and large. Increasing the number and density of recording channels could enable the collection of richer motor/sensory information, and may enhance the precision of decoding and increase opportunities for controlling external devices. Several reports have aimed to increase the number and density of channels. However, few studies have discussed the actual validity of high-density ECoG arrays. In this study, we developed novel high-density flexible ECoG arrays and conducted decoding analyses with monkey somatosensory evoked potentials (SEPs). Using MEMS technology, we made 96-channel Parylene electrode arrays with an inter-electrode distance of 700 μm and recording site area of 350 μm2. The arrays were mainly placed onto the finger representation area in the somatosensory cortex of the macaque, and partially inserted into the central sulcus. With electrical finger stimulation, we successfully recorded and visualized finger SEPs with a high spatiotemporal resolution. We conducted offline analyses in which the stimulated fingers and intensity were predicted from recorded SEPs using a support vector machine. We obtained the following results: (1) Very high accuracy (~98%) was achieved with just a short segment of data (~15 ms from stimulus onset). (2) High accuracy (~96%) was achieved even when only a single channel was used. This result indicated placement optimality for decoding. (3) Higher channel counts generally improved prediction accuracy, but the efficacy was small for predictions with feature vectors that included time-series information. These results suggest that ECoG signals with high spatiotemporal resolution could enable greater decoding precision or external device control.

The challenge of this work is to study the design and development of human-robot collaboration (HRC) in cellular manufacturing. Based on the concept of human collaborative design, four main design factors are being identified and developed in an active HRC prototype production cell for cable harness assembly. Human collaborative design aims to optimize the system design for the advantage of collaboration between human and robots based on human considerations. Task modeling approach is developed to study and analyze the task in order to identify the collaboration tasks to develop the collaboration planning. In the collaboration safety development, five safety designs, cover both hardware and control design, are proposed and developed in the prototype system. Risk assessment is conducted to verify the safety design. Two main experiments were conducted as preliminary study to investigate mental workload in HRC. A multimodal information support system is developed in the study of man-machine interface in this work to provide a comprehensive human-robot interface to facilitate human operator. The system performance evaluation had proven the improvement of prototype production cell with HRC design for cellular manufacturing.

To examine how delay-period activity participates in the decision of a saccade direction, we analyzed prefrontal activity while monkeys performed 2 tasks: oculomotor delayed-response (ODR) and self-selection ODR (S-ODR) tasks. In the ODR task, monkeys were required to make a memory-guided saccade to the cue location after a 3-s delay. In the S-ODR task, 4 identical visual cues were presented simultaneously during the cue period and monkeys were required to make a saccade in any one direction after the delay. Delay-period activity was observed in both tasks in the same neuron with similar directional preferences. Neurons with delay-period activity were classified into several groups based on the temporal pattern of the activity itself and of the strength of the directional selectivity. Among these, neurons with an increasing type of delay-period activity with persistent directional selectivity throughout the delay period in the ODR task also showed directional delay-period activity in the S-ODR task. These results indicate that an increasing type of delay-period activity, which is thought to represent motor information, plays an important role in generating and enhancing directional bias in the S-ODR task and therefore contributes significantly to the decision process of the saccade direction in the S-ODR task.

The study of dual-task performance in human subjects has received considerable interest in cognitive neuroscience because it can provide detailed insights into the neural mechanisms underlying higher-order cognitive control. Despite many decades of research, our understanding of the neurobiological basis of dual-task performance is still limited, and some critical questions are still under debate. Recently, behavioral and neurophysiological studies of dual-task performance in animals have begun to provide intriguing evidence regarding how dual-task information is processed in the brain. In this review, we first summarize key evidence in neuroimaging and neuropsychological studies in humans and discuss possible reasons for discrepancies across studies. We then provide a comprehensive review of the literature on dual-task studies in animals and provide a novel working hypothesis that may reconcile the divergent results in human studies toward a unified view of the mechanisms underlying dual-task processing. Finally, we propose possible directions for future dual-task experiments in the framework of comparative cognitive neuroscience.

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