Periaqueductal gray neurons encode the sequential motor program in hunting behavior of mice

Sequential encoding of motor programs is essential for behavior generation. However, whether it is critical for instinctive behavior is still largely unknown. Mouse hunting behavior typically contains a sequential motor program, including the prey search, chase, attack, and consumption. Here, we reveal that the neuronal activity in the lateral periaqueductal gray (LPAG) follows a sequential pattern and is time-locked to different hunting actions. Optrode recordings and photoinhibition demonstrate that LPAGVgat neurons are required for the prey detection, chase and attack, while LPAGVglut2 neurons are selectively required for the attack. Ablation of inputs that could trigger hunting, including the central amygdala, the lateral hypothalamus, and the zona incerta, interrupts the activity sequence pattern and substantially impairs hunting actions. Therefore, our findings reveal that periaqueductal gray neuronal ensembles encode the sequential hunting motor program, which might provide a framework for decoding complex instinctive behaviors.

Depth-resolved intersubject functional correlation of 7T BOLD signals reveals increased stimulus related information sharing across deep layers in premotor and parietal nodes for predictable actions

While the brain regions involved in action observation are relatively well documented in humans and primates, how these regions communicate to help understand and predict actions remains poorly understood. Traditional views emphasized a feed-forward architecture in which visual features are organized into increasingly complex representations that feed onto motor programs in parietal and then premotor cortices where the matching of observed actions upon the observer's own motor programs contributes to action understanding. Predictive coding models place less emphasis on feed-forward connections and propose that feed-back connections from premotor regions back to parietal and visual neurons represent predictions about upcoming actions that can supersede visual inputs when actions become predictable, with visual input then merely representing prediction errors. Here we leverage the notion that feed-back connections target deeper cortical layers than feed-forward connections to help adjudicate across these views. Specifically, we test whether observing sequences of hand actions in their natural order, which permits participants to predict upcoming actions, triggers more feed-back input to parietal regions than seeing the same actions in a scrambled sequence that hinders making predictions. Using submillimeter fMRI acquisition at 7T, we find that watching predictable sequences triggers more action-related activity (as measured using intersubject functional correlation) in deep layers of the parietal cortical area PFt than watching the exact same actions in scrambled and hence unpredictable sequence. In addition, functional connectivity analysis performed using intersubject functional connectivity confirms that this deep, action-related signals in PFt could originate from ventral premotor region BA44. This data showcases the utility of intersubject functional correlation in combination with 7T MRI to explore the architecture of social cognition under more naturalistic conditions, and provides evidence for models that emphasize the importance of feed-back connections in action prediction.

Bimanual thumb-index finger indications of noncorresponding extents

Two experiments tested a prediction derived from the recent finding that the Oppel-Kundt illusion – the overestimation of a filled extent relative to an empty one – was much attenuated when the empty part of a bipartite row of dots was vertical and the filled part horizontal, suggesting that the Horizontal-vertical illusion – the overestimation of vertical extents relative to horizontal ones – only acted on the empty part of an Oppel-Kundt figure. Observers had to bimanually indicate the sizes of the two parts of an Oppel-Kundt figure, which were arranged one above the other with one part vertical and the other part tilted -45°, 0°, or 45°. Results conformed to the prediction but response bias was greater when observers had been instructed to point to the extents’ endpoints than when instructed to estimate the extents’ lengths, suggesting that different concepts and motor programs had been activated.

What information is being acquired during the period of Quiet Eye? Comment on Vickers

Sports and athletes’ highest performance offer a fascinating scenario to investigate perceptual-motor expertise. The remarkable work of Joan Vickers has captured this opportunity and built a valuable experimental paradigm. Our commentary emphasizes what information is being acquired during the period of Quiet Eye (QE), capable to produce successful performance. First, an extended notion of visual system that includes posture is presented. It is suggested that QE would represent a collective postural effort (resulting from movements of eyes, head, trunk, and whole body) to acquire the relevant information available in the optic flow. Second, the contribution of neural structures and functioning for vision and attention is discussed. Models of neural networks of attention and two visual systems are described with respect to QE and some questions about action parameters and motor programs are raised.

Handwriting in Alzheimer’s Disease

Background: Agraphia is a typical feature in the clinical course of Alzheimer’s disease (AD). Objective: Assess the differences between AD and normal aging as regards kinematographic features of handwriting and elucidate writing deficits in AD. Methods: The study included 23 patients with AD (78.09 years/SD = 7.12; MMSE 21.39/SD = 3.61) and 34 healthy controls (75.56 years/SD = 5.85; MMSE 29.06/SD = 0.78). Both groups performed alphabetical and non-alphabetical writing tasks. The kinematographic assessment included the average number of inversions per stroke (NIV; number of peaks in the velocity profile in a single up or down stroke), percentage of automated segments, frequency (average number of strokes per second), writing pressure, and writing velocity on paper. Results: A total of 14 patients showed overt writing difficulties reflected by omissions or substitutions of letters. AD patients showed less automated movements (as measured by NIV), lower writing velocity, and lower frequency of up-and-down strokes in non-alphabetical as well as in alphabetical writing. In the patient group, Spearman correlation analysis between overt writing performance and NIV was significant. That means patients who had less errors in writing a sentence showed a higher automaticity in handwriting. The correctness of alphabetical writing and some kinematographic measures in writing non-alphabetical material reached excellent diagnostic values in ROC analyses. There was no difference in the application of pressure on the pen between patients and controls. Conclusion: Writing disorders are multi-componential in AD and not strictly limited to one processing level. The slow and poorly automated execution of motor programs is not bound to alphabetical material.

STOPPING A CONTINUOUS MOVEMENT: A NOVEL APPROACH TO INVESTIGATING MOTOR CONTROL

Flexible, adaptive behavior is critically dependent on inhibitory control. For example, if you suddenly notice you are about to step on a tack and would prefer not to, the ability to halt your ongoing movement is critical. To address limitations in existing approaches for studying your ability to rapidly terminate your movement ('stopping'), we developed a novel stop task. This task requires termination of ongoing motor programs, provides a direct measure of SSRT, and allows for comparison of the same behavior (stopping) in conditions that elicit either prepared or reactive inhibitory control. Here, we present and evaluate our novel Continuous Movement Stop Task (CMST). We examined several versions of the task in a total of 49 participants. Our data reveal that the CMST is effectively able to dissociate stopping behavior between the planned and unplanned conditions. Additionally, within the subset of participants for which we measured speed, we found that participants initiated stopping (with respect to the stop signal) significantly earlier on planned stop compared to unplanned stop trials. Finally, participants took longer to arrive at full motor arrest (i.e. SSRT) following stop initiation on planned than on unplanned stop trials. This novel task design will enable a more precise quantification of stopping behavior and, in conjunction with neuroscientific methods, could provide more rigorous characterization of brain networks underlying stopping.

Abstract Neural Representations of Category Membership beyond Information Coding Stimulus or Response

For decades, researchers have debated whether mental representations are symbolic or grounded in sensory inputs and motor programs. Certainly, aspects of mental representations are grounded. However, does the brain also contain abstract concept representations that mediate between perception and action in a flexible manner not tied to the details of sensory inputs and motor programs? Such conceptual pointers would be useful when concepts remain constant despite changes in appearance and associated actions. We evaluated whether human participants acquire such representations using fMRI. Participants completed a probabilistic concept learning task in which sensory, motor, and category variables were not perfectly coupled or entirely independent, making it possible to observe evidence for abstract representations or purely grounded representations. To assess how the learned concept structure is represented in the brain, we examined brain regions implicated in flexible cognition (e.g., pFC and parietal cortex) that are most likely to encode an abstract representation removed from sensory–motor details. We also examined sensory–motor regions that might encode grounded sensory–motor-based representations tuned for categorization. Using a cognitive model to estimate participants' category rule and multivariate pattern analysis of fMRI data, we found the left pFC and MT coded for category in the absence of information coding for stimulus or response. Because category was based on the stimulus, finding an abstract representation of category was not inevitable. Our results suggest that certain brain areas support categorization behavior by constructing concept representations in a format akin to a symbol that differs from stimulus–motor codes.

Roles of the prefrontal cortex in learning to time the onset of pre-existing motor programs

The prefrontal cortex (PFC) is involved in cognitive control of motor activities and timing of future intensions. This study investigated the cognitive control of balance recovery in response to unpredictable gait perturbations and the role of PFC subregions in learning by repetition. Bilateral dorsolateral (DLPFC), ventrolateral (VLPFC), frontopolar (FPFC) and orbitofrontal (OFC) cortex hemodynamic changes induced by unpredictable slips were analyzed as a function of successive trials in ten healthy young adults. Slips were induced by the acceleration of one belt as the participant walked on a split-belt treadmill. A portable functional near-infrared spectroscope monitored PFC activities quantified by oxyhemoglobin (ΔO2Hb) and deoxyhemoglobin (ΔHbR) during the consecutive trial phases: standing, walking, slip-recovery. During the first 3 trials, the average oxyhemoglobin (ΔO2Hbavg) in the DLPFC, VLPFC, FPFC, and OFC cortex was significantly higher during slip-recovery than unperturbed walking or the standing baseline. Then, ΔO2Hbavg decreased progressively from trial-to-trial in the DLPFC, VLPFC, and FPFC, but increased and then remained constant in the OFC. The average deoxyhemoglobin (ΔHbRavg) presented mirror patterns. These changes after the third trial were paralleled by the progressive improvement of recovery revealed by kinematic variables. The results corroborate our previous hypothesis that only timing of the onset of a “good enough recovery motor program” is learned with practice. They also strongly support the assumption that the PFC contributes to the recall of pre-existing motor programs whose onset timing is adjusted by the OFC. Hence, learning is clearly divided into two steps delineated by the switch in activity of the OFC. Additionally, motor processes appear to share the working memory as well as decisional and predictive resources of the cognitive system.