Neural mechanisms of movement planning: motor cortex and beyond

Sex differences in prelimbic cortex calcium dynamics during stress and fear learning

In recent years, research has progressively increased the importance of considering sex differences in stress and fear memory studies. Many studies have traditionally focused on male subjects, potentially overlooking critical differences with females. Emerging evidence suggests that males and females can exhibit distinct behavioral and neurophysiological responses to stress and fear conditioning. These differences may be attributable to variations in hormone levels, brain structure, and neural circuitry, particularly in regions such as the prefrontal cortex (PFC). In the present study, we explored sex differences in prelimbic cortex (PL) calcium activity in animals submitted to immobilization stress (IMO), fear conditioning (FC), and fear extinction (FE). While no significant sex differences were found in behavioral responses, we did observe differences in several PL calcium activity parameters. To determine whether these results were related to behaviors beyond stress and fear memory, we conducted correlation studies between the movement of the animals and PL activity during IMO and freezing behavior during FC and FE. Our findings revealed a clear correlation between PL calcium activity with movement during stress exposure and freezing behavior, with no sex differences observed in these correlations. These results suggest a significant role for the PL in movement and locomotion, in addition to its involvement in fear-related processes. The inclusion of both female and male subjects is crucial for studies like this to fully understand the role of the PFC and other brain areas in stress and fear responses. Recognizing sex differences enhances our comprehension of brain function and can lead to more personalized and effective approaches in the study and treatment of stress and fear-related conditions.

Learning and Control in Motor Cortex across Cell Types and Scales

The motor cortex is essential for controlling the flexible movements underlying complex behaviors. Behavioral flexibility involves the ability to integrate and refine new movements, thereby expanding an animal's repertoire. This review discusses recent strides in motor learning mechanisms across spatial and temporal scales, describing how neural networks are remodeled at the level of synapses, cell types, and circuits and across time as animals' learn new skills. It highlights how changes at each scale contribute to the evolving structure and function of neural circuits that accompanies the expansion and refinement of motor skills. We review new findings highlighted by advanced imaging techniques that have opened new vistas in optical physiology and neuroanatomy, revealing the complexity and adaptability of motor cortical circuits, crucial for learning and control. At the structural level, we explore the dynamic regulation of dendritic spines mediating corticocortical and thalamocortical inputs to the motor cortex. We delve into the role of perisynaptic astrocyte processes in maintaining synaptic stability during learning. We also examine the functional diversity among pyramidal neuron subtypes, their dendritic computations and unique contributions to single cell and network function. Further, we highlight how cortical activation is characterized by increased consistency and reduced strength as new movements are learned and how external inputs contribute to these changes. Finally, we consider the motor cortex's necessity as movements unfold over long time scales. These insights will continue to drive new research directions, enhancing our understanding of motor cortical circuit transformations that underpin behavioral changes expressed throughout an animal's life.

An intense electrical stimulus can elicit a StartReact effect but with decreased incidence and later onset of the startle reflex

Planned actions can be triggered involuntarily by a startling acoustic stimulus (SAS), resulting in very short reaction times (RT). This phenomenon, known as the StartReact effect, is thought to result from the startle-related activation of reticular structures. However, other sensory modalities also can elicit a reflexive startle response. Here, we assessed the effectiveness of an intense startling electric stimulus (SES) in eliciting the StartReact effect as compared to a SAS. We tested SES intensities at 15 and 25 times the perceptual threshold of each participant, as well as SAS intensities of 114 dB and 120 dB. The electrical stimulation electrodes were placed over short head of the biceps brachii on the arm not involved in the task. Intense electric and acoustic stimuli were presented on 20% of the trials in a simple RT paradigm requiring a targeted ballistic wrist extension movement. The proportion of trials showing short latency (≤ 120 ms) startle reflex-related activation in sternocleidomastoid was significantly lower on intense electrical stimulus trials compared to intense acoustic trials, and the startle response onset occurred significantly later on SES trials compared to SAS. However, when a startle reflex was observed, RTs related to the prepared movement were facilitated to a similar extent for both SES and SAS conditions, suggesting that the accelerated response latency associated with the StartReact effect is independent of stimulus type.

Muscle spindles provide flexible sensory feedback for movement sequences

Sensory feedback is essential for motor performance and must adapt to task demands. Muscle spindle afferents (MSAs) are a major primary source of feedback about movement, and their responses are readily modulated online by gain-controller fusimotor neurons and other mechanisms. They are therefore a powerful site for implementing flexible sensorimotor control. We recorded from MSAs innervating the jaw musculature during performance of a directed lick sequence task. Jaw MSAs encoded complex jaw-tongue kinematics. However, kinematic encoding alone accounted for less than half of MSA spiking variability. MSA representations of kinematics changed based on sequence progression (beginning, middle, or end of the sequence, or reward consumption), suggesting that MSAs are flexibly tuned across the task. Dynamic control of incoming feedback signals from MSAs may be a strategy for adaptable sensorimotor control during performance of complex behaviors.

The influence of traditional Chinese exercise on brain function compared with other sports: A meta-analysis on functional neuroimaging studies

Traditional Chinese Exercise (TCE) has been shown to improve quality of life, and functional magnetic resonance imaging (fMRI) is a highly used method for investigating its mechanism. However, there is currently a lack of systematic reviews and meta-analyses focusing on TCE-related brain changes. This study aims to fill this gap by conducting a meta-analysis on brain changes of TCE with fMRI technology. We searched relevant studies published until February 2024. Independent researchers conducted literature screening, quality assessment, and clinical and neuroimaging data extraction. Focis were filtered from eligible studies, and meta-analysis was performed using seed-based d mapping. Twenty-three studies involving 1182 participants were included in this study. The result found that longitudinal TCE increased brain activity in the left anterior cingulate gyri, right fusiform gyrus, right middle temporal gyrus, left middle occipital gyrus and left frontal superior compared with other exercises or healthcare. Subgroup analysis showed that the brain activity in the right superior frontal gyrus dorsolateral; right cortico-spinal projections; corpus callosum; right inferior network; right gyrus rectus; left middle occipital gyrus were decreased after TCE compared to other exercise among healthy participants. The right median cingulate gyri was increased after Baduanjin (one of the TCE) compared to other exercise; the left precentral gyrus activity was increased after Tai chi chuan (TCC) practice compared to other exercise. The brain activity in the right insula, right supplementary motor area, and left anterior thalamic were significantly increased after long-time TCC exercise. TCE effectively improved the cognitive level of the subjects. Among them, the MoCA score increased, but Memory Quotient was not improved. Research results indicate that TCE have specific neuromodulatory effects, and different TCE have different neuromodulatory patterns.

Network state changes in sensory thalamus represent learned outcomes

Thalamic brain areas play an important role in adaptive behaviors. Nevertheless, the population dynamics of thalamic relays during learning across sensory modalities remain unknown. Using a cross-modal sensory reward-associative learning paradigm combined with deep brain two-photon calcium imaging of large populations of auditory thalamus (medial geniculate body, MGB) neurons in male mice, we identified that MGB neurons are biased towards reward predictors independent of modality. Additionally, functional classes of MGB neurons aligned with distinct task periods and behavioral outcomes, both dependent and independent of sensory modality. During non-sensory delay periods, MGB ensembles developed coherent neuronal representation as well as distinct co-activity network states reflecting predicted task outcome. These results demonstrate flexible cross-modal ensemble coding in auditory thalamus during adaptive learning and highlight its importance in brain-wide cross-modal computations during complex behavior.

Dynamic control of sequential retrieval speed in networks with heterogeneous learning rules

Temporal rescaling of sequential neural activity has been observed in multiple brain areas during behaviors involving time estimation and motor execution at variable speeds. Temporally asymmetric Hebbian rules have been used in network models to learn and retrieve sequential activity, with characteristics that are qualitatively consistent with experimental observations. However, in these models sequential activity is retrieved at a fixed speed. Here, we investigate the effects of a heterogeneity of plasticity rules on network dynamics. In a model in which neurons differ by the degree of temporal symmetry of their plasticity rule, we find that retrieval speed can be controlled by varying external inputs to the network. Neurons with temporally symmetric plasticity rules act as brakes and tend to slow down the dynamics, while neurons with temporally asymmetric rules act as accelerators of the dynamics. We also find that such networks can naturally generate separate 'preparatory' and 'execution' activity patterns with appropriate external inputs.

Dynamics of directional motor tuning in the primate premotor and primary motor cortices during sensorimotor learning

Sensorimotor learning requires reorganization of neuronal activity in the premotor cortex (PM) and primary motor cortex (M1). To reveal PM- and M1-specific reorganization in a primate, we conducted calcium imaging in common marmosets while they learned a two-target reaching (pull/push) task after mastering a one-target reaching (pull) task. Throughout learning of the two-target reaching task, the dorsorostral PM (PMdr) showed peak activity earlier than the dorsocaudal PM (PMdc) and M1. During learning, the reaction time in pull trials increased and correlated strongly with the peak timing of PMdr activity. PMdr showed decreasing representation of newly introduced (push) movement, whereas PMdc and M1 maintained high representation of pull and push movements. Many task-related neurons in PMdc and M1 exhibited a strong preference to either movement direction. PMdc neurons dynamically switched their preferred direction depending on their performance in push trials in the early learning stage, whereas M1 neurons stably retained their preferred direction and high similarity of preferred direction between neighbors. These results suggest that in primate sensorimotor learning, dynamic directional motor tuning in PMdc converts the sensorimotor association formed in PMdr to the stable and specific motor representation of M1.

Neural underpinnings of fine motor skills under stress and anxiety: A review

This review offers a comprehensive examination of how stress and anxiety affect motor behavior, particularly focusing on fine motor skills and gait adaptability. We explore the role of several neurochemicals, including brain-derived neurotrophic factor (BDNF) and dopamine, in modulating neural plasticity and motor control under these affective states. The review highlights the importance of developing therapeutic strategies that enhance motor performance by leveraging the interactions between key neurochemicals. Additionally, we investigate the complex interplay between emotional-cognitive states and sensorimotor behaviors, showing how stress and anxiety disrupt neural integration, leading to impairments in skilled movements and negatively impacting quality of life. Synthesizing evidence from human and rodent studies, we provide a detailed understanding of the relationships among stress, anxiety, and motor behavior. Our findings reveal neurophysiological pathways, behavioral outcomes, and potential therapeutic targets, emphasizing the intricate connections between neurobiological mechanisms, environmental factors, and motor performance.

Classification of Mild Cognitive Impairment and Alzheimer's Disease Using Manual Motor Measures

INTRODUCTION

Manual motor problems have been reported in mild cognitive impairment (MCI) and Alzheimer's disease (AD), but the specific aspects that are affected, their neuropathology, and potential value for classification modeling is unknown. The current study examined if multiple measures of motor strength, dexterity, and speed are affected in MCI and AD, related to AD biomarkers, and are able to classify MCI or AD.

METHODS

Fifty-three cognitively normal (CN), 33 amnestic MCI, and 28 AD subjects completed five manual motor measures: grip force, Trail Making Test A, spiral tracing, finger tapping, and a simulated feeding task. Analyses included (1) group differences in manual performance; (2) associations between manual function and AD biomarkers (PET amyloid β, hippocampal volume, and APOE ε4 alleles); and (3) group classification accuracy of manual motor function using machine learning.

RESULTS

Amnestic MCI and AD subjects exhibited slower psychomotor speed and AD subjects had weaker dominant hand grip strength than CN subjects. Performance on these measures was related to amyloid β deposition (both) and hippocampal volume (psychomotor speed only). Support vector classification well-discriminated control and AD subjects (area under the curve of 0.73 and 0.77, respectively) but poorly discriminated MCI from controls or AD.

CONCLUSION

Grip strength and spiral tracing appear preserved, while psychomotor speed is affected in amnestic MCI and AD. The association of motor performance with amyloid β deposition and atrophy could indicate that this is due to amyloid deposition in and atrophy of motor brain regions, which generally occurs later in the disease process. The promising discriminatory abilities of manual motor measures for AD emphasize their value alongside other cognitive and motor assessment outcomes in classification and prediction models, as well as potential enrichment of outcome variables in AD clinical trials.

Rule-based modulation of a sensorimotor transformation across cortical areas

Flexible responses to sensory stimuli based on changing rules are critical for adapting to a dynamic environment. However, it remains unclear how the brain encodes and uses rule information to guide behavior. Here, we made single-unit recordings while head-fixed mice performed a cross-modal sensory selection task where they switched between two rules: licking in response to tactile stimuli while rejecting visual stimuli, or vice versa. Along a cortical sensorimotor processing stream including the primary (S1) and secondary (S2) somatosensory areas, and the medial (MM) and anterolateral (ALM) motor areas, single-neuron activity distinguished between the two rules both prior to and in response to the tactile stimulus. We hypothesized that neural populations in these areas would show rule-dependent preparatory states, which would shape the subsequent sensory processing and behavior. This hypothesis was supported for the motor cortical areas (MM and ALM) by findings that (1) the current task rule could be decoded from pre-stimulus population activity; (2) neural subspaces containing the population activity differed between the two rules; and (3) optogenetic disruption of pre-stimulus states impaired task performance. Our findings indicate that flexible action selection in response to sensory input can occur via configuration of preparatory states in the motor cortex.

A combinatorial neural code for long-term motor memory

Motor skill repertoire can be stably retained over long periods, but the neural mechanism underlying stable memory storage remains poorly understood. Moreover, it is unknown how existing motor memories are maintained as new motor skills are continuously acquired. Here we tracked neural representation of learned actions throughout a significant portion of a mouse's lifespan, and we show that learned actions are stably retained in motor memory in combination with context, which protects existing memories from erasure during new motor learning. We used automated home-cage training to establish a continual learning paradigm in which mice learned to perform directional licking in different task contexts. We combined this paradigm with chronic two-photon imaging of motor cortex activity for up to 6 months. Within the same task context, activity driving directional licking was stable over time with little representational drift. When learning new task contexts, new preparatory activity emerged to drive the same licking actions. Learning created parallel new motor memories while retaining the previous memories. Re-learning to make the same actions in the previous task context re-activated the previous preparatory activity, even months later. At the same time, continual learning of new task contexts kept creating new preparatory activity patterns. Context-specific memories, as we observed in the motor system, may provide a solution for stable memory storage throughout continual learning. Learning in new contexts produces parallel new representations instead of modifying existing representations, thus protecting existing motor repertoire from erasure.

Whole-brain Mapping of Inputs and Outputs of Specific Orbitofrontal Cortical Neurons in Mice

The orbitofrontal cortex (ORB), a region crucial for stimulus-reward association, decision-making, and flexible behaviors, extensively connects with other brain areas. However, brain-wide inputs to projection-defined ORB neurons and the distribution of inhibitory neurons postsynaptic to neurons in specific ORB subregions remain poorly characterized. Here we mapped the inputs of five types of projection-specific ORB neurons and ORB outputs to two types of inhibitory neurons. We found that different projection-defined ORB neurons received inputs from similar cortical and thalamic regions, albeit with quantitative variations, particularly in somatomotor areas and medial groups of the dorsal thalamus. By counting parvalbumin (PV) or somatostatin (SST) interneurons innervated by neurons in specific ORB subregions, we found a higher fraction of PV neurons in sensory cortices and a higher fraction of SST neurons in subcortical regions targeted by medial ORB neurons. These results provide insights into understanding and investigating the function of specific ORB neurons.

Effect of spaceflight experience on human brain structure, microstructure, and function: systematic review of neuroimaging studies

Spaceflight-induced brain changes have been commonly reported in astronauts. The role of microgravity in the alteration of the brain structure, microstructure, and function can be tested with magnetic resonance imaging (MRI) techniques. Here, we aim to provide a comprehensive overview of Spaceflight studies exploring the potential role of brain alterations identified by MRI in astronauts. We conducted a search on PubMed, Web of Science, and Scopus to find neuroimaging correlates of spaceflight experience using MRI. A total of 20 studies (structural MRI n = 8, diffusion-based MRI n = 2, functional MRI n = 1, structural MRI and diffusion-weighted MRI n = 6, structural MRI and functional MRI n = 3) met our inclusion criteria. Overall, the studies showed that regardless of the MRI techniques, mission duration significantly impacts the human brain, prompting the inclusion of various brain regions as features in the analyses. After spaceflight, notable alterations were also observed in the superior occipital gyrus and the precentral gyrus which show alterations in connectivity and activation during spaceflight. The results provided highlight the alterations in brain structure after spaceflight, the unique patterns of brain remodeling, the challenges in drawing unified conclusions, and the impact of microgravity on intracranial cerebrospinal fluid volume.

Effect of task-oriented training assisted by force feedback hand rehabilitation robot on finger grasping function in stroke patients with hemiplegia: a randomised controlled trial

BACKGROUND

Over 80% of patients with stroke experience finger grasping dysfunction, affecting independence in activities of daily living and quality of life. In routine training, task-oriented training is usually used for functional hand training, which may improve finger grasping performance after stroke, while augmented therapy may lead to a better treatment outcome. As a new technology-supported training, the hand rehabilitation robot provides opportunities to improve the therapeutic effect by increasing the training intensity. However, most hand rehabilitation robots commonly applied in clinics are based on a passive training mode and lack the sensory feedback function of fingers, which is not conducive to patients completing more accurate grasping movements. A force feedback hand rehabilitation robot can compensate for these defects. However, its clinical efficacy in patients with stroke remains unknown. This study aimed to investigate the effectiveness and added value of a force feedback hand rehabilitation robot combined with task-oriented training in stroke patients with hemiplegia.

METHODS

In this single-blinded randomised controlled trial, 44 stroke patients with hemiplegia were randomly divided into experimental (n = 22) and control (n = 22) groups. Both groups received 40 min/day of conventional upper limb rehabilitation training. The experimental group received 20 min/day of task-oriented training assisted by a force feedback rehabilitation robot, and the control group received 20 min/day of task-oriented training assisted by therapists. Training was provided for 4 weeks, 5 times/week. The Fugl-Meyer motor function assessment of the hand part (FMA-Hand), Action Research Arm Test (ARAT), grip strength, Modified Ashworth scale (MAS), range of motion (ROM), Brunnstrom recovery stages of the hand (BRS-H), and Barthel index (BI) were used to evaluate the effect of two groups before and after treatment.

RESULTS

Intra-group comparison: In both groups, the FMA-Hand, ARAT, grip strength, AROM, BRS-H, and BI scores after 4 weeks of treatment were significantly higher than those before treatment (p < 0.05), whereas there was no significant difference in finger flexor MAS scores before and after treatment (p > 0.05). Inter-group comparison: After 4 weeks of treatment, the experimental group's FMA-Hand total score, ARAT, grip strength, and AROM were significantly better than those of the control group (p < 0.05). However, there were no statistically significant differences in the scores of each sub-item of the FMA-Hand after Bonferroni correction (p > 0.007). In addition, there were no statistically significant differences in MAS, BRS-H, and BI scores (p > 0.05).

CONCLUSION

Hand performance improved in patients with stroke after 4 weeks of task-oriented training. The use of a force feedback hand rehabilitation robot to support task-oriented training showed additional value over conventional task-oriented training in stroke patients with hand dysfunction.

CLINICAL TRIAL REGISTRATION INFORMATION

NCT05841108.

Cholecystokinin facilitates motor skill learning by modulating neuroplasticity in the motor cortex

Cholecystokinin (CCK) is an essential modulator for neuroplasticity in sensory and emotional domains. Here, we investigated the role of CCK in motor learning using a single pellet reaching task in mice. Mice with a knockout of Cck gene (Cck-/-) or blockade of CCK-B receptor (CCKBR) showed defective motor learning ability; the success rate of retrieving reward remained at the baseline level compared to the wildtype mice with significantly increased success rate. We observed no long-term potentiation upon high-frequency stimulation in the motor cortex of Cck-/- mice, indicating a possible association between motor learning deficiency and neuroplasticity in the motor cortex. In vivo calcium imaging demonstrated that the deficiency of CCK signaling disrupted the refinement of population neuronal activity in the motor cortex during motor skill training. Anatomical tracing revealed direct projections from CCK-expressing neurons in the rhinal cortex to the motor cortex. Inactivation of the CCK neurons in the rhinal cortex that project to the motor cortex bilaterally using chemogenetic methods significantly suppressed motor learning, and intraperitoneal application of CCK4, a tetrapeptide CCK agonist, rescued the motor learning deficits of Cck-/- mice. In summary, our results suggest that CCK, which could be provided from the rhinal cortex, may surpport motor skill learning by modulating neuroplasticity in the motor cortex.

Preparatory activity and the expansive null-space

The study of the cortical control of movement experienced a conceptual shift over recent decades, as the basic currency of understanding shifted from single-neuron tuning towards population-level factors and their dynamics. This transition was informed by a maturing understanding of recurrent networks, where mechanism is often characterized in terms of population-level factors. By estimating factors from data, experimenters could test network-inspired hypotheses. Central to such hypotheses are 'output-null' factors that do not directly drive motor outputs yet are essential to the overall computation. In this Review, we highlight how the hypothesis of output-null factors was motivated by the venerable observation that motor-cortex neurons are active during movement preparation, well before movement begins. We discuss how output-null factors then became similarly central to understanding neural activity during movement. We discuss how this conceptual framework provided key analysis tools, making it possible for experimenters to address long-standing questions regarding motor control. We highlight an intriguing trend: as experimental and theoretical discoveries accumulate, the range of computational roles hypothesized to be subserved by output-null factors continues to expand.

Separating cognitive and motor processes in the behaving mouse

The cognitive processes supporting complex animal behavior are closely associated with ubiquitous movements responsible for our posture, facial expressions, ability to actively sample our sensory environments, and other critical processes. These movements are strongly related to neural activity across much of the brain and are often highly correlated with ongoing cognitive processes, making it challenging to dissociate the neural dynamics that support cognitive processes from those supporting related movements. In such cases, a critical issue is whether cognitive processes are separable from related movements, or if they are driven by common neural mechanisms. Here, we demonstrate how the separability of cognitive and motor processes can be assessed, and, when separable, how the neural dynamics associated with each component can be isolated. We establish a novel two-context behavioral task in mice that involves multiple cognitive processes and show that commonly observed dynamics taken to support cognitive processes are strongly contaminated by movements. When cognitive and motor components are isolated using a novel approach for subspace decomposition, we find that they exhibit distinct dynamical trajectories. Further, properly accounting for movement revealed that largely separate populations of cells encode cognitive and motor variables, in contrast to the 'mixed selectivity' often reported. Accurately isolating the dynamics associated with particular cognitive and motor processes will be essential for developing conceptual and computational models of neural circuit function and evaluating the function of the cell types of which neural circuits are composed.

Striatal dopamine release tracks the relationship between actions and their consequences

The acquisition and performance of goal-directed actions has long been argued to depend on the integration of glutamatergic inputs to the posterior dorsomedial striatum (pDMS) under the modulatory influence of dopamine. Nevertheless, relatively little is known about the dynamics of striatal dopamine during goal-directed actions. To investigate this, we chronically recorded dopamine release in the pDMS as rats acquired two actions for distinct outcomes as these action-outcome associations were incremented and then subsequently degraded or reversed. We found that bilateral dopamine release scaled with action value, whereas the lateralized dopamine signal, i.e., the difference in dopamine release ipsilaterally and contralaterally to the direction of the goal-directed action, reflected the strength of the action-outcome association independently of changes in movement. Our results establish, therefore, that striatal dopamine activity during goal-directed action reflects both bilateral moment-to-moment changes in action value and the long-term action-outcome association.

FABEL: Forecasting Animal Behavioral Events with Deep Learning-Based Computer Vision

Behavioral neuroscience aims to provide a connection between neural phenomena and emergent organism-level behaviors. This requires perturbing the nervous system and observing behavioral outcomes, and comparing observed post-perturbation behavior with predicted counterfactual behavior and therefore accurate behavioral forecasts. In this study we present FABEL, a deep learning method for forecasting future animal behaviors and locomotion trajectories from historical locomotion alone. We train an offline pose estimation network to predict animal body-part locations in behavioral video; then sequences of pose vectors are input to deep learning time-series forecasting models. Specifically, we train an LSTM network that predicts a future food interaction event in a specified time window, and a Temporal Fusion Transformer that predicts future trajectories of animal body-parts, which are then converted into probabilistic label forecasts. Importantly, accurate prediction of food interaction provides a basis for neurobehavioral intervention in the context of compulsive eating. We show promising results on forecasting tasks between 100 milliseconds and 5 seconds timescales. Because the model takes only behavioral video as input, it can be adapted to any behavioral task and does not require specific physiological readouts. Simultaneously, these deep learning models may serve as extensible modules that can accommodate diverse signals, such as in-vivo fluorescence imaging and electrophysiology, which may improve behavior forecasts and elucidate invervention targets for desired behavioral change.

Rule-based modulation of a sensorimotor transformation across cortical areas

Flexible responses to sensory stimuli based on changing rules are critical for adapting to a dynamic environment. However, it remains unclear how the brain encodes rule information and uses this information to guide behavioral responses to sensory stimuli. Here, we made single-unit recordings while head-fixed mice performed a cross-modal sensory selection task in which they switched between two rules in different blocks of trials: licking in response to tactile stimuli applied to a whisker while rejecting visual stimuli, or licking to visual stimuli while rejecting the tactile stimuli. Along a cortical sensorimotor processing stream including the primary (S1) and secondary (S2) somatosensory areas, and the medial (MM) and anterolateral (ALM) motor areas, the single-trial activity of individual neurons distinguished between the two rules both prior to and in response to the tactile stimulus. Variable rule-dependent responses to identical stimuli could in principle occur via appropriate configuration of pre-stimulus preparatory states of a neural population, which would shape the subsequent response. We hypothesized that neural populations in S1, S2, MM and ALM would show preparatory activity states that were set in a rule-dependent manner to cause processing of sensory information according to the current rule. This hypothesis was supported for the motor cortical areas by findings that (1) the current task rule could be decoded from pre-stimulus population activity in ALM and MM; (2) neural subspaces containing the population activity differed between the two rules; and (3) optogenetic disruption of pre-stimulus states within ALM and MM impaired task performance. Our findings indicate that flexible selection of an appropriate action in response to a sensory input can occur via configuration of preparatory states in the motor cortex.

Optimizing electrode placement for transcranial direct current stimulation in nonsuperficial cortical regions: a computational modeling study

Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique for modulating neuronal excitability by sending a weak current through electrodes attached to the scalp. For decades, the conventional tDCS electrode for stimulating the superficial cortex has been widely reported. However, the investigation of the optimal electrode to effectively stimulate the nonsuperficial cortex is still lacking. In the current study, the optimal tDCS electrode montage that can deliver the maximum electric field to nonsuperficial cortical regions is investigated. Two finite element head models were used for computational simulation to determine the optimal montage for four different nonsuperficial regions: the left foot motor cortex, the left dorsomedial prefrontal cortex (dmPFC), the left medial orbitofrontal cortex (mOFC), and the primary visual cortex (V1). Our findings showed a good consistency in the optimal montage between two models, which led to the anode and cathode being attached to C4-C3 for the foot motor, F4-F3 for the dmPFC, Fp2-F7 for the mOFC, and Oz-Cz for V1. Our suggested montages are expected to enhance the overall effectiveness of stimulation of nonsuperficial cortical areas.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13534-023-00335-2.

The effects of mental fatigue on fine motor performance in humans and its neural network connectivity mechanism: a dart throwing study

While it is well known that mental fatigue impairs fine motor performance, the investigation into its neural basis remains scant. Here, we investigate the impact of mental fatigue on fine motor performance and explore its underlying neural network connectivity mechanisms. A total of 24 healthy male university students were recruited and randomly divided into two groups: a mental fatigue group (MF) and a control group (Control). Both groups completed 50 dart throws, while electroencephalography (EEG) data were collected. Following the Stroop intervention, participants in the MF group exhibited a decrease in Stroop task accuracy and throwing performance, and an increase in reaction time along with VAS and NASA scores. The EEG data during dart-throwing revealed that the network connectivity strength of theta oscillations in the frontal and left central regions was significantly higher in the MF group compared with the Control group, while the network connectivity strength of alpha oscillations in the left parietal region was significantly enhanced. The interregional connectivity within the theta and alpha rhythm bands, particularly in the frontal-central-parietal network connections, also showed a significant increase in the MF group. Mental fatigue impairs dart throwing performance and is accompanied by increased connectivity in alpha and theta.

Modeling and dissociation of intrinsic and input-driven neural population dynamics underlying behavior

Neural dynamics can reflect intrinsic dynamics or dynamic inputs, such as sensory inputs or inputs from other brain regions. To avoid misinterpreting temporally structured inputs as intrinsic dynamics, dynamical models of neural activity should account for measured inputs. However, incorporating measured inputs remains elusive in joint dynamical modeling of neural-behavioral data, which is important for studying neural computations of behavior. We first show how training dynamical models of neural activity while considering behavior but not input or input but not behavior may lead to misinterpretations. We then develop an analytical learning method for linear dynamical models that simultaneously accounts for neural activity, behavior, and measured inputs. The method provides the capability to prioritize the learning of intrinsic behaviorally relevant neural dynamics and dissociate them from both other intrinsic dynamics and measured input dynamics. In data from a simulated brain with fixed intrinsic dynamics that performs different tasks, the method correctly finds the same intrinsic dynamics regardless of the task while other methods can be influenced by the task. In neural datasets from three subjects performing two different motor tasks with task instruction sensory inputs, the method reveals low-dimensional intrinsic neural dynamics that are missed by other methods and are more predictive of behavior and/or neural activity. The method also uniquely finds that the intrinsic behaviorally relevant neural dynamics are largely similar across the different subjects and tasks, whereas the overall neural dynamics are not. These input-driven dynamical models of neural-behavioral data can uncover intrinsic dynamics that may otherwise be missed.

Roles of the cerebellar vermis in predictive postural controls against external disturbances

The central nervous system predictively controls posture against external disturbances; however, the detailed mechanisms remain unclear. We tested the hypothesis that the cerebellar vermis plays a substantial role in acquiring predictive postural control by using a standing task with floor disturbances in rats. The intact, lesioned, and sham groups of rats sequentially underwent 70 conditioned floor-tilting trials, and kinematics were recorded. Six days before these recordings, only the lesion group underwent focal suction surgery targeting vermal lobules IV-VIII. In the naïve stage of the sequential trials, the upright postures and fluctuations due to the disturbance were mostly consistent among the groups. Although the pattern of decrease in postural fluctuation due to learning corresponded among the groups, the learning rate estimated from the lumbar displacement was significantly lower in the lesion group than in the intact and sham groups. These results suggest that the cerebellar vermis contributes to predictive postural controls.

The Associative Thalamus: A Switchboard for Cortical Operations and a Promising Target for Schizophrenia

Schizophrenia is a brain disorder that profoundly perturbs cognitive processing. Despite the success in treating many of its symptoms, the field lacks effective methods to measure and address its impact on reasoning, inference, and decision making. Prefrontal cortical abnormalities have been well documented in schizophrenia, but additional dysfunction in the interactions between the prefrontal cortex and thalamus have recently been described. This dysfunction may be interpreted in light of parallel advances in neural circuit research based on nonhuman animals, which show critical thalamic roles in maintaining and switching prefrontal activity patterns in various cognitive tasks. Here, we review this basic literature and connect it to emerging innovations in clinical research. We highlight the value of focusing on associative thalamic structures not only to better understand the very nature of cognitive processing but also to leverage these circuits for diagnostic and therapeutic development in schizophrenia. We suggest that the time is right for building close bridges between basic thalamic research and its clinical translation, particularly in the domain of cognition and schizophrenia.

Task learning is subserved by a domain-general brain network

One of the most important human faculties is the ability to acquire not just new memories but the capacity to perform entirely new tasks. However, little is known about the brain mechanisms underlying the learning of novel tasks. Specifically, it is unclear to what extent learning of different tasks depends on domain-general and/or domain-specific brain mechanisms. Here human subjects (n = 45) learned to perform 6 new tasks while undergoing functional MRI. The different tasks required the engagement of perceptual, motor, and various cognitive processes related to attention, expectation, speed-accuracy tradeoff, and metacognition. We found that a bilateral frontoparietal network was more active during the initial compared with the later stages of task learning, and that this effect was stronger for task variants requiring more new learning. Critically, the same frontoparietal network was engaged by all 6 tasks, demonstrating its domain generality. Finally, although task learning decreased the overall activity in the frontoparietal network, it increased the connectivity strength between the different nodes of that network. These results demonstrate the existence of a domain-general brain network whose activity and connectivity reflect learning for a variety of new tasks, and thus may underlie the human capacity for acquiring new abilities.

Distributed and specific encoding of sensory, motor, and decision information in the mouse neocortex during goal-directed behavior

Goal-directed behaviors involve coordinated activity in many cortical areas, but whether the encoding of task variables is distributed across areas or is more specifically represented in distinct areas remains unclear. Here, we compared representations of sensory, motor, and decision information in the whisker primary somatosensory cortex, medial prefrontal cortex, and tongue-jaw primary motor cortex in mice trained to lick in response to a whisker stimulus with mice that were not taught this association. Irrespective of learning, properties of the sensory stimulus were best encoded in the sensory cortex, whereas fine movement kinematics were best represented in the motor cortex. However, movement initiation and the decision to lick in response to the whisker stimulus were represented in all three areas, with decision neurons in the medial prefrontal cortex being more selective, showing minimal sensory responses in miss trials and motor responses during spontaneous licks. Our results reconcile previous studies indicating highly specific vs. highly distributed sensorimotor processing.

Simultaneous, cortex-wide and cellular-resolution neuronal population dynamics reveal an unbounded scaling of dimensionality with neuron number

The brain's remarkable properties arise from collective activity of millions of neurons. Widespread application of dimensionality reduction to multi-neuron recordings implies that neural dynamics can be approximated by low-dimensional "latent" signals reflecting neural computations. However, what would be the biological utility of such a redundant and metabolically costly encoding scheme and what is the appropriate resolution and scale of neural recording to understand brain function? Imaging the activity of one million neurons at cellular resolution and near-simultaneously across mouse cortex, we demonstrate an unbounded scaling of dimensionality with neuron number. While half of the neural variance lies within sixteen behavior-related dimensions, we find this unbounded scaling of dimensionality to correspond to an ever-increasing number of internal variables without immediate behavioral correlates. The activity patterns underlying these higher dimensions are fine-grained and cortex-wide, highlighting that large-scale recording is required to uncover the full neural substrates of internal and potentially cognitive processes.

Cell type-specific connectome predicts distributed working memory activity in the mouse brain

Recent advances in connectomics and neurophysiology make it possible to probe whole-brain mechanisms of cognition and behavior. We developed a large-scale model of the multiregional mouse brain for a cardinal cognitive function called working memory, the brain's ability to internally hold and process information without sensory input. The model is built on mesoscopic connectome data for interareal cortical connections and endowed with a macroscopic gradient of measured parvalbumin-expressing interneuron density. We found that working memory coding is distributed yet exhibits modularity; the spatial pattern of mnemonic representation is determined by long-range cell type-specific targeting and density of cell classes. Cell type-specific graph measures predict the activity patterns and a core subnetwork for memory maintenance. The model shows numerous attractor states, which are self-sustained internal states (each engaging a distinct subset of areas). This work provides a framework to interpret large-scale recordings of brain activity during cognition, while highlighting the need for cell type-specific connectomics.

Dissociating the Contributions of Frontal Eye Field Activity to Spatial Working Memory and Motor Preparation

Neurons within dorsolateral prefrontal cortex (PFC) of primates are characterized by robust persistent spiking activity exhibited during the delay period of working memory tasks. This includes the frontal eye field (FEF) where nearly half of the neurons are active when spatial locations are held in working memory. Past evidence has established the FEF's contribution to the planning and triggering of saccadic eye movements as well as to the control of visual spatial attention. However, it remains unclear whether persistent delay activity reflects a similar dual role in movement planning and visuospatial working memory. We trained male monkeys to alternate between different forms of a spatial working memory task which could dissociate remembered stimulus locations from planned eye movements. We tested the effects of inactivation of FEF sites on behavioral performance in the different tasks. Consistent with previous studies, FEF inactivation impaired the execution of memory-guided saccades (MGSs), and impaired performance when remembered locations matched the planned eye movement. In contrast, memory performance was largely unaffected when the remembered location was dissociated from the correct eye movement response. Overall, the inactivation effects demonstrated clear deficits in eye movements, regardless of task type, but little or no evidence of a deficit in spatial working memory. Thus, our results indicate that persistent delay activity in the FEF contributes primarily to the preparation of eye movements and not to spatial working memory.SIGNIFICANCE STATEMENT Many frontal eye field (FEF) neurons exhibit spatially tuned persistent spiking activity during the delay period of working memory tasks. However, the role of the FEF in spatial working memory remains unresolved. We tested the effects of inactivation of FEF sites on behavioral performance in different forms of a spatial working memory task, one of which dissociated the remembered stimulus locations from planned eye movements. We found that FEF inactivation produced clear deficits in eye movements, regardless of task type, but no deficit in spatial working memory when dissociated from those movements.

Superior colliculus bidirectionally modulates choice activity in frontal cortex

Action selection occurs through competition between potential choice options. Neural correlates of choice competition are observed across frontal cortex and downstream superior colliculus (SC) during decision-making, yet how these regions interact to mediate choice competition remains unresolved. Here we report that SC can bidirectionally modulate choice competition and drive choice activity in frontal cortex. In the mouse, topographically matched regions of frontal cortex and SC formed a descending motor pathway for directional licking and a re-entrant loop via the thalamus. During decision-making, distinct neuronal populations in both frontal cortex and SC encoded opposing lick directions and exhibited competitive interactions. SC GABAergic neurons encoded ipsilateral choice and locally inhibited glutamatergic neurons that encoded contralateral choice. Activating or suppressing these cell types could bidirectionally drive choice activity in frontal cortex. These results thus identify SC as a major locus to modulate choice competition within the broader action selection network.

Activity map of a cortico-cerebellar loop underlying motor planning

The neocortex and cerebellum interact to mediate cognitive functions. It remains unknown how the two structures organize into functional networks to mediate specific behaviors. Here we delineate activity supporting motor planning in relation to the mesoscale cortico-cerebellar connectome. In mice planning directional licking based on short-term memory, preparatory activity instructing future movement depends on the anterior lateral motor cortex (ALM) and the cerebellum. Transneuronal tracing revealed divergent and largely open-loop connectivity between the ALM and distributed regions of the cerebellum. A cerebellum-wide survey of neuronal activity revealed enriched preparatory activity in hotspot regions with conjunctive input-output connectivity to the ALM. Perturbation experiments show that the conjunction regions were required for maintaining preparatory activity and correct subsequent movement. Other cerebellar regions contributed little to motor planning despite input or output connectivity to the ALM. These results identify a functional cortico-cerebellar loop and suggest the cerebellar cortex selectively establishes reciprocal cortico-cerebellar communications to orchestrate motor planning.

The rat frontal orienting field dynamically encodes value for economic decisions under risk

Frontal and parietal cortex are implicated in economic decision-making, but their causal roles are untested. Here we silenced the frontal orienting field (FOF) and posterior parietal cortex (PPC) while rats chose between a cued lottery and a small stable surebet. PPC inactivations produced minimal short-lived effects. FOF inactivations reliably reduced lottery choices. A mixed-agent model of choice indicated that silencing the FOF caused a change in the curvature of the rats' utility function (U = Vρ). Consistent with this finding, single-neuron and population analyses of neural activity confirmed that the FOF encodes the lottery value on each trial. A dynamical model, which accounts for electrophysiological and silencing results, suggests that the FOF represents the current lottery value to compare against the remembered surebet value. These results demonstrate that the FOF is a critical node in the neural circuit for the dynamic representation of action values for choice under risk.

Increased functional connectivity coupling with supplementary motor area in blepharospasm at rest

OBJECTIVE

To explore the abnormalities of brain function in blepharospasm (BSP) and to illustrate its neural mechanisms by assuming supplementary motor area (SMA) as the entry point.

METHODS

Twenty-five patients with BSP and 23 controls underwent resting-state functional MRI, seed-based functional connectivity (FC), correlation analysis, receiver operating characteristic curve (ROC) analysis, and support vector machine (SVM) were applied to process the data.

RESULTS

Patients showed that the left medial prefrontal cortex (MPFC), left lingual gyrus, right cerebellar crus I, and right lingual gyrus/cerebellar crus I had enhanced FC with the left SMA, whereas the right inferior temporal gyrus (ITG) had enhanced FC with the right SMA relative to controls. The FC between the left MPFC and left SMA was positively correlated with symptomatic severity. The ROC analysis verified that the abnormal FCs demonstrated in this study can separate patients and controls at high sensitivity and specificity. SVM analysis exhibited that combined FCs of the left SMA were optimal for distinguishing patients and control group at the accuracy of 89.58%, with sensitivity of 92.00% and specificity of 86.96%.

CONCLUSIONS

Several brain networks partake in the neurobiology of BSP. SMA plays a vital role in several brain networks and might be the key pathogenic factor in BSP.

SIGNIFICANCE

Providing novel evidence for the engagement of the MPFC in the motor symptoms of BSP, enhancing credibility of the thesis that SMA regulates the neurobiology of BSP, and providing ideas of screening susceptible population of BSP using neuroimaging.

The Secondary Motor Cortex-striatum Circuit Contributes to Suppressing Inappropriate Responses in Perceptual Decision Behavior

The secondary motor cortex (M2) encodes choice-related information and plays an important role in cue-guided actions. M2 neurons innervate the dorsal striatum (DS), which also contributes to decision-making behavior, yet how M2 modulates signals in the DS to influence perceptual decision-making is unclear. Using mice performing a visual Go/No-Go task, we showed that inactivating M2 projections to the DS impaired performance by increasing the false alarm (FA) rate to the reward-irrelevant No-Go stimulus. The choice signal of M2 neurons correlated with behavioral performance, and the inactivation of M2 neurons projecting to the DS reduced the choice signal in the DS. By measuring and manipulating the responses of direct or indirect pathway striatal neurons defined by M2 inputs, we found that the indirect pathway neurons exhibited a shorter response latency to the No-Go stimulus, and inactivating their early responses increased the FA rate. These results demonstrate that the M2-to-DS pathway is crucial for suppressing inappropriate responses in perceptual decision behavior.

A motor plan is accessible for voluntary initiation and involuntary triggering at similar short latencies

Movement goals are an essential component of motor planning, altering voluntary and involuntary motor actions. While there have been many studies of motor planning, it is unclear if motor goals influence voluntary and involuntary movements at similar latencies. The objectives of this study were to determine how long it takes to prepare a motor action and to compare this time for voluntary and involuntary movements. We hypothesized a prepared motor action would influence voluntarily and involuntarily initiated movements at the same latency. We trained subjects to reach with a forced reaction time paradigm and used a startling acoustic stimulus (SAS) to trigger involuntary initiation of the same reaches. The time available to prepare was controlled by varying when one of four reach targets was presented. Reach direction was used to evaluate accuracy. We quantified the time between target presentation and the cue or trigger for movement initiation. We found that reaches were accurately initiated when the target was presented 48 ms before the SAS and 162 ms before the cue to voluntarily initiate movement. While the SAS precisely controlled the latency of movement onset, voluntary reach onset was more variable. We, therefore, quantified the time between target presentation and movement onset and found no significant difference in the time required to plan reaches initiated voluntarily or involuntarily (∆ = 8 ms, p = 0.2). These results demonstrate that the time required to plan accurate reaches is similar regardless of if they are initiated voluntarily or triggered involuntarily. This finding may inform the understanding of neural pathways governing storage and access of motor plans.

Behavioral measurements of motor readiness in mice

Motor planning facilitates rapid and precise execution of volitional movements. Although motor planning has been classically studied in humans and monkeys, the mouse has become an increasingly popular model system to study neural mechanisms of motor planning. It remains yet untested whether mice and primates share common behavioral features of motor planning. We combined videography and a delayed response task paradigm in an autonomous behavioral system to measure motor planning in non-body-restrained mice. Motor planning resulted in both reaction time (RT) savings and increased movement accuracy, replicating classic effects in primates. We found that motor planning was reflected in task-relevant body features. Both the specific actions prepared and the degree of motor readiness could be read out online during motor planning. The online readout further revealed behavioral evidence of simultaneous preparation for multiple actions under uncertain conditions. These results validate the mouse as a model to study motor planning, demonstrate body feature movements as a powerful real-time readout of motor readiness, and offer behavioral evidence that motor planning can be a parallel process that permits rapid selection of multiple prepared actions.

Altered Thalamocortical Signaling in a Mouse Model of Parkinson's Disease

Activation of the primary motor cortex (M1) is important for the execution of skilled movements and motor learning, and its dysfunction contributes to the pathophysiology of Parkinson's disease (PD). A well-accepted idea in PD research, albeit not tested experimentally, is that the loss of midbrain dopamine leads to decreased activation of M1 by the motor thalamus. Here, we report that midbrain dopamine loss altered motor thalamus input in a laminar- and cell type-specific fashion and induced laminar-specific changes in intracortical synaptic transmission. Frequency-dependent changes in synaptic dynamics were also observed. Our results demonstrate that loss of midbrain dopaminergic neurons alters thalamocortical activation of M1 in both male and female mice, and provide novel insights into circuit mechanisms for motor cortex dysfunction in a mouse model of PD.SIGNIFICANCE STATEMENT Loss of midbrain dopamine neurons increases inhibition from the basal ganglia to the motor thalamus, suggesting that it may ultimately lead to reduced activation of primary motor cortex (M1). In contrast with this line of thinking, analysis of M1 activity in patients and animal models of Parkinson's disease report hyperactivation of this region. Our results are the first report that midbrain dopamine loss alters the input-output function of M1 through laminar and cell type specific effects. These findings support and expand on the idea that loss of midbrain dopamine reduces motor cortex activation and provide experimental evidence that reconciles reduced thalamocortical input with reports of altered activation of motor cortex in patients with Parkinson's disease.

Sex-dependent noradrenergic modulation of premotor cortex during decision-making

Rodent premotor cortex (M2) integrates information from sensory and cognitive networks for action planning during goal-directed decision-making. M2 function is regulated by cortical inputs and ascending neuromodulators, including norepinephrine (NE) released from the locus coeruleus (LC). LC-NE has been shown to modulate the signal-to-noise ratio of neural representations in target cortical regions, increasing the salience of relevant stimuli. Using rats performing a two-alternative forced choice task after administration of a β-noradrenergic antagonist (propranolol), we show that β-noradrenergic signaling is necessary for effective action plan signals in anterior M2. Loss of β-noradrenergic signaling results in failure to suppress irrelevant action plans in anterior M2 disrupting decoding of cue-related information, delaying decision times, and increasing trial omissions, particularly in females. Furthermore, we identify a potential mechanism for the sex bias in behavioral and neural changes after propranolol administration via differential expression of β2 noradrenergic receptor RNA across sexes in anterior M2, particularly on local inhibitory neurons. Overall, we show a critical role for β-noradrenergic signaling in anterior M2 during decision-making by suppressing irrelevant information to enable efficient action planning and decision-making.

Functional MRI Lateralization [M1] of dlPFC and Implications for Transcranial Magnetic Stimulation (TMS) Targeting

The present study investigates a potential method of optimizing effective strategies for the functional lateralization of the dorsolateral prefrontal cortex (dlPFC) while in a scanner. Effective hemisphere lateralization of the dlPFC is crucial for lowering the functional risks connected to specific interventions (such as neurosurgery and transcranial magnetic stimulation (TMS), as well as increasing the effectiveness of a given intervention by figuring out the optimal location. This task combines elements of creative problem solving, executive decision making based on an internal rule set, and working memory. A retrospective analysis was performed on a total of 58 unique participants (34 males, 24 females, Mage = 42.93 years, SDage = 16.38). Of these participants, 47 were classified as right-handed, 7 were classified as left-handed, and 4 were classified as ambidextrous, according to the Edinburgh Handedness Inventory. The imaging data were qualitatively judged by two trained, blinded investigators (neurologist and neuropsychologist) for dominant handedness (primary motor cortex) and dominant dorsolateral prefrontal cortex (dlPFC). The results demonstrated that 21.4% of right-handed individuals showed a dominant dlPFC localized to the right hemisphere rather than the assumed left, and 16.7% of left-handers were dominant in their left hemisphere. The task completed in the scanner might be an efficient method for localizing a potential dlPFC target for the purpose of brain stimulation (e.g., TMS), though further study replications are needed to extend and validate these findings.

Whole brain inputs to major descending pathways of the anterior lateral motor cortex

The anterior lateral motor cortex (ALM) is critical to subsequent correct movements and plays a vital role in predicting specific future movements. Different descending pathways of the ALM are preferentially involved in different roles in movements. However, the circuit function mechanisms of these different pathways may be concealed in the anatomy circuit. Clarifying the anatomy inputs of these pathways should provide some helpful information for elucidating these function mechanisms. Here, we used a retrograde trans-synaptic rabies virus to systematically generate, analyze, and compare whole brain maps of inputs to the thalamus (TH)-, medulla oblongata (Med)-, superior colliculus (SC)-, and pontine nucleus (Pons)-projecting ALM neurons in C57BL/6J mice. Fifty-nine separate regions from nine major brain areas projecting to the descending pathways of the ALM were identified. Brain-wide quantitative analyses revealed identical whole brain input patterns between these descending pathways. Most inputs to the pathways originated from the ipsilateral side of the brain, with most innervations provided by the cortex and TH. The contralateral side of the brain also sent sparse projections, but these were rare, emanating only from the cortex and cerebellum. Nevertheless, the inputs received by TH-, Med-, SC-, and Pons-projecting ALM neurons had different weights, potentially laying an anatomical foundation for understanding the diverse functions of well-defined descending pathways of the ALM. Our findings provide anatomical information to help elucidate the precise connections and diverse functions of the ALM.NEW & NOTEWORTHY Distinct descending pathways of anterior lateral motor cortex (ALM) share common inputs. These inputs are with varied weights. Most inputs were from the ipsilateral side of brain. Preferential inputs were provided by cortex and thalamus (TH).

Age-related decline of online visuomotor adaptation: a combined effect of deteriorations of motor anticipation and execution

The literature has established that the capability of visuomotor adaptation decreases with aging. However, the underlying mechanisms of this decline are yet to be fully understood. The current study addressed this issue by examining how aging affected visuomotor adaptation in a continuous manual tracking task with delayed visual feedback. To distinguish separate contributions of the declined capability of motor anticipation and deterioration of motor execution to this age-related decline, we recorded and analyzed participants' manual tracking performances and their eye movements during tracking. Twenty-nine older people and twenty-three young adults (control group) participated in this experiment. The results showed that the age-related decline of visuomotor adaptation was strongly linked to degraded performance in predictive pursuit eye movement, indicating that declined capability motor anticipation with aging had critical influences on the age-related decline of visuomotor adaptation. Additionally, deterioration of motor execution, measured by random error after controlling for the lag between target and cursor, was found to have an independent contribution to the decline of visuomotor adaptation. Taking these findings together, we see a picture that the age-related decline of visuomotor adaptation is a joint effect of the declined capability of motor anticipation and the deterioration of motor execution with aging.

Dissociating the Contributions of Frontal Eye Field Activity to Spatial Working Memory and Motor Preparation

Neurons within dorsolateral prefrontal cortex of primates are characterized by robust persistent spiking activity exhibited during the delay period of working memory tasks. This includes the frontal eye field (FEF) where nearly half of the neurons are active when spatial locations are held in working memory. Past evidence has established the FEF's contribution to the planning and triggering of saccadic eye movements as well as to the control of visual spatial attention. However, it remains unclear if persistent delay activity reflects a similar dual role in movement planning and visuospatial working memory. We trained monkeys to alternate between different forms of a spatial working memory task which could dissociate remembered stimulus locations from planned eye movements. We tested the effects of inactivation of FEF sites on behavioral performance in the different tasks. Consistent with previous studies, FEF inactivation impaired the execution of memory-guided saccades, and impaired performance when remembered locations matched the planned eye movement. In contrast, memory performance was largely unaffected when the remembered location was dissociated from the correct eye movement response. Overall, the inactivation effects demonstrated clear deficits on eye movements, regardless of task type, but little or no evidence of a deficit in spatial working memory. Thus, our results indicate that persistent delay activity in the FEF contributes primarily to the preparation of eye movements and not to spatial working memory.

Mobile cognition: imaging the human brain in the 'real world'

Cognitive neuroscience studies in humans have enabled decades of impactful discoveries but have primarily been limited to recording the brain activity of immobile participants in a laboratory setting. In recent years, advances in neuroimaging technologies have enabled recordings of human brain activity to be obtained during freely moving behaviours in the real world. Here, we propose that these mobile neuroimaging methods can provide unique insights into the neural mechanisms of human cognition and contribute to the development of novel treatments for neurological and psychiatric disorders. We further discuss the challenges associated with studying naturalistic human behaviours in complex real-world settings as well as strategies for overcoming them. We conclude that mobile neuroimaging methods have the potential to bring about a new era of cognitive neuroscience in which neural mechanisms can be studied with increased ecological validity and with the ability to address questions about natural behaviour and cognitive processes in humans engaged in dynamic real-world experiences.

A proprioceptive feedback circuit drives Caenorhabditis elegans locomotor adaptation through dopamine signaling

An animal adapts its motor behavior to navigate the external environment. This adaptation depends on proprioception, which provides feedback on an animal's body postures. How proprioception mechanisms interact with motor circuits and contribute to locomotor adaptation remains unclear. Here, we describe and characterize proprioception-mediated homeostatic control of undulatory movement in the roundworm Caenorhabditis elegans. We found that the worm responds to optogenetically or mechanically induced decreases in midbody bending amplitude by increasing its anterior amplitude. Conversely, it responds to increased midbody amplitude by decreasing the anterior amplitude. Using genetics, microfluidic and optogenetic perturbation response analyses, and optical neurophysiology, we elucidated the neural circuit underlying this compensatory postural response. The dopaminergic PDE neurons proprioceptively sense midbody bending and signal to AVK interneurons via the D2-like dopamine receptor DOP-3. The FMRFamide-like neuropeptide FLP-1, released by AVK, regulates SMB head motor neurons to modulate anterior bending. We propose that this homeostatic behavioral control optimizes locomotor efficiency. Our findings demonstrate a mechanism in which proprioception works with dopamine and neuropeptide signaling to mediate motor control, a motif that may be conserved in other animals.

Role of auditory-somatosensory corticothalamic circuit integration in analgesia

Our sensory environment is permeated by a diverse array of auditory and somatosensory stimuli. The pairing of acoustic signals with concurrent or forthcoming tactile cues are abundant in everyday life and various survival contexts across species, thus deeming the ability to integrate sensory inputs arising from the combination of these stimuli as crucial. The corticothalamic system plays a critical role in orchestrating the construction, integration and distribution of the information extracted from these sensory modalities. In this mini-review, we provide a circuit-level description of the auditory corticothalamic pathway in conjunction with adjacent corticothalamic somatosensory projections. Although the extent of the functional interactions shared by these pathways is not entirely elucidated, activation of each of these systems appears to modulate sensory perception in the complementary domain. Several specific issues are reviewed. Under certain environmental noise conditions, the spectral information of a sound could induce modulations in nociception and even induce analgesia. We begin by discussing recent findings by Zhou et al. (2022) implicating the corticothalamic system in mediating sound-induced analgesia. Next, we describe relevant components of the corticothalamic pathway's functional organization. Additionally, we describe an emerging body of literature pointing to intrathalamic circuitry being optimal for controlling and selecting sensory signals across modalities, with the thalamic reticular nucleus being a candidate mechanism for directing cross-modal interactions. Finally, Ca2+ bursting in thalamic neurons evoked by the thalamic reticular nucleus is explored.

Motor cortex projections to red and pontine nuclei have distinct roles during movement in the mouse

Motor control largely depends on the deep layer 5 (L5) pyramidal neurons that project to subcortical structures. However, it is largely unknown if these neurons are functionally segregated with distinct roles in movement performance. Here, we analyzed mouse motor cortex L5 pyramidal neurons projecting to the red and pontine nuclei during movement preparation and execution. Using photometry to analyze the calcium activity of L5 pyramidal neurons projecting to the red nucleus and pons, we reveal that both types of neurons activate with different temporal dynamics. Optogenetic inhibition of either kind of projection differentially affects forelimb movement onset and execution in a lever press task, but only the activity of corticopontine neurons is significantly correlated with trial-by-trial variations in reaction time. The results indicate that cortical neurons projecting to the red and pontine nuclei contribute differently to sensorimotor integration, suggesting that L5 output neurons are functionally compartmentalized generating, in parallel, different downstream information.

Superior colliculus cell types bidirectionally modulate choice activity in frontal cortex

Action selection occurs through competition between potential choice options. Neural correlates of choice competition are observed across frontal cortex and downstream superior colliculus (SC) during decision-making, yet how these regions interact to mediate choice competition remains unresolved. Here we report that cell types within SC can bidirectionally modulate choice competition and drive choice activity in frontal cortex. In the mouse, topographically matched regions of frontal cortex and SC formed a descending motor pathway for directional licking and a re-entrant loop via the thalamus. During decision-making, distinct neuronal populations in both frontal cortex and SC encoded opposing lick directions and exhibited push-pull dynamics. SC GABAergic neurons encoded ipsilateral choice and glutamatergic neurons encoded contralateral choice, and activating or suppressing these cell types could bidirectionally drive push-pull choice activity in frontal cortex. These results thus identify SC as a major locus to modulate choice competition within the broader action selection network.

Evaluate the efficacy and reliability of functional gradients in within-subject designs

The cerebral cortex is characterized as the integration of distinct functional principles that correspond to basic primary functions, such as vision and movement, and domain-general functions, such as attention and cognition. Diffusion embedding approach is a novel tool to describe transitions between different functional principles, and has been successively applied to investigate pathological conditions in between-group designs. What still lacking and urgently needed is the efficacy of this method to differentiate within-subject circumstances. In this study, we applied the diffusion embedding to eyes closed (EC) and eyes on (EO) resting-state conditions from 145 participants. We found significantly lower within-network dispersion of visual network (VN) (p = 7.3 × 10^-4 ) as well as sensorimotor network (SMN) (p = 1 × 10^-5 ) and between-network dispersion of VN (p = 2.3 × 10^-4 ) under EC than EO, while frontoparietal network (p = 9.2 × 10^-4 ) showed significantly higher between-network dispersion during EC than EO. Test-retest reliability analysis further displayed fair reliability (intraclass correlation coefficient [ICC] < 0.4) of the network dispersions (mean ICC = 0.116 ± 0.143 [standard deviation]) except for the within-network dispersion of SMN under EO (ICC = 0.407). And the reliability under EO was higher but not significantly higher than reliability under EC. Our study demonstrated that the diffusion embedding approach that shows fair reliability is capable of distinguishing EC and EO resting-state conditions, such that this method could be generalized to other within-subject designs.