Inhibition of protein synthesis in M1 of monkeys disrupts performance of sequential movements guided by memory

Choosing the optimal target area for repeated transcranial magnetic stimulation in treating neuropathic pain in spinal cord injury patients: a comparative analysis

Objective

The specific target area of repeated transcranial magnetic stimulation (rTMS) in treating neuropathic pain resulting from spinal cord injury (SCI-NP) remains uncertain.

Methods

Thirty-four participants with SCI-NP were allocated into three groups, namely, the motor cortex (M1, A) group, the left dorsolateral prefrontal cortex (LDLPFC, B) group, and the control (sham stimulation, C) group. The intervention was administered totally 10 times. Outcome measures assessed pre-(T0) and post-(T1)intervention, including Numerical Rating scale (NRS), anxiety (SAS), depression (SDS), sleep quality (PSQI), brief pain inventory (BPI), and impression of change.

Results

All outcomes in groups A and B significantly changed after intervention (p < 0.05), and the delta value (T1-T0) also significantly changed than group C (p < 0.05). The delta value of SDS in the group B was better than the group A, and the change of pain degree in the group B was moderately correlated with the change in PSQI (r = 0.575, p < 0.05). Both patients in the groups A and B showed significant impression of change about their received therapy (p < 0.05).

Conclusion

Both targets are effective, but LDLPFC is more effective in reducing depression in SCI-NP. Healthcare providers might select the suitable area according to the specific attributes of their patients.

Variational relevance evaluation of individual fMRI data enables deconstruction of task-dependent neural dynamics

In neuroimaging research, univariate analysis has always been used to localize "representations" at the microscale, whereas network approaches have been applied to characterize transregional "operations". How are representations and operations linked through dynamic interactions? We developed the variational relevance evaluation (VRE) method to analyze individual task fMRI data, which selects informative voxels during model training to localize the "representation", and quantifies the dynamic contributions of single voxels across the whole-brain to different cognitive functions to characterize the "operation". Using 15 individual fMRI data files for higher visual area localizers, we evaluated the characterization of selected voxel positions of VRE and revealed different object-selective regions functioning in similar dynamics. Using another 15 individual fMRI data files for memory retrieval after offline learning, we found similar task-related regions working in different neural dynamics for tasks with diverse familiarities. VRE demonstrates a promising horizon in individual fMRI research.

Reconsidering Meat Intake and Human Health: A Review of Current Research

Meat consumption is gradually increasing and its impact on health has attracted widespread attention, resulting in epidemiological studies proposing a reduction in meat and processed meat intake. This review briefly summarizes recent advances in understanding the effects of meat or processed meat on human health, as well as the underlying mechanisms. Meat consumption varies widely among individuals, populations, and regions, with higher consumption in developed countries than in developing countries. However, increasing meat consumption may not be the main cause of increasing incidence of chronic disease, since the development of chronic disease is a complex physiological process that involves many factors, including excessive total energy intake and changes in food digestion processes, gut microbiota composition, and liver metabolism. In comparison, unhealthy dietary habits and a sedentary lifestyle with decreasing energy expenditure are factors more worthy of reflection. Meat and meat products provide high-value protein and many key essential micronutrients. In short, as long as excessive intake and overprocessing of meats are avoided, meat remains an indispensable source of nutrition for human health.

Dopaminergic modulation of primary motor cortex: From cellular and synaptic mechanisms underlying motor learning to cognitive symptoms in Parkinson's disease

The primary motor cortex (M1) is crucial for movement execution, especially dexterous ones, but also for cognitive functions like motor learning. The acquisition of motor skills to execute dexterous movements requires dopamine-dependent and -independent plasticity mechanisms within M1. In addition to the basal ganglia, M1 is disturbed in Parkinson's disease (PD). However, little is known about how the lack of dopamine (DA), characteristic of PD, directly or indirectly impacts M1 circuitry. Here we review data from studies of PD patients and the substantial research in non-human primate and rodent models of DA depletion. These models enable us to understand the importance of DA in M1 physiology at the behavioral, network, cellular, and synaptic levels. We first summarize M1 functions and neuronal populations in mammals. We then look at the origin of M1 DA and the cellular location of its receptors and explore the impact of DA loss on M1 physiology, motor, and executive functions. Finally, we discuss how PD treatments impact M1 functions.

The integrative role of the M1 in motor sequence learning

The primary motor cortex (M1) is crucial in motor learning. Whether the M1 encodes the motor engram for sequential finger tapping formed by an emphasis on speed is still inconclusive. The active states of engrams are hard to discriminate from the motor execution per se. As preparatory activity reflects the upcoming movement parameters, we hypothesized that the retrieval of motor engrams generated by different learning modes is reflected as a learning-related increase in the preparatory activity of the M1. To test this hypothesis, we evaluated the preparatory activity during the learning of sequential finger-tapping with the non-dominant left hand using a 7T functional MRI. Participants alternated between performing a tapping sequence as quickly as possible (maximum mode) or at a constant speed of 2 Hz paced by a sequence-specifying visual cue (constant mode). We found a training-related increase in preparatory activity in the network covering the bilateral anterior intraparietal sulcus and inferior parietal lobule extending to the right M1 during the maximum mode and the right M1 during the constant mode. These findings indicate that the M1, as the last effector of the motor output, integrates the motor engram distributed through the networks despite training mode differences.

The Roles of the Cortical Motor Areas in Sequential Movements

The ability to learn and perform a sequence of movements is a key component of voluntary motor behavior. During the learning of sequential movements, individuals go through distinct stages of performance improvement. For instance, sequential movements are initially learned relatively fast and later learned more slowly. Over multiple sessions of repetitive practice, performance of the sequential movements can be further improved to the expert level and maintained as a motor skill. How the brain binds elementary movements together into a meaningful action has been a topic of much interest. Studies in human and non-human primates have shown that a brain-wide distributed network is active during the learning and performance of skilled sequential movements. The current challenge is to identify a unique contribution of each area to the complex process of learning and maintenance of skilled sequential movements. Here, I bring together the recent progress in the field to discuss the distinct roles of cortical motor areas in this process.

Neural manifold under plasticity in a goal driven learning behaviour

Neural activity is often low dimensional and dominated by only a few prominent neural covariation patterns. It has been hypothesised that these covariation patterns could form the building blocks used for fast and flexible motor control. Supporting this idea, recent experiments have shown that monkeys can learn to adapt their neural activity in motor cortex on a timescale of minutes, given that the change lies within the original low-dimensional subspace, also called neural manifold. However, the neural mechanism underlying this within-manifold adaptation remains unknown. Here, we show in a computational model that modification of recurrent weights, driven by a learned feedback signal, can account for the observed behavioural difference between within- and outside-manifold learning. Our findings give a new perspective, showing that recurrent weight changes do not necessarily lead to change in the neural manifold. On the contrary, successful learning is naturally constrained to a common subspace.

Sequential Reaching Task for the Study of Motor Skills in Monkeys

The ability to perform a sequence of movements is a key component of motor skills, such as typing or playing a musical instrument. How the brain binds elementary movements together into meaningful actions has been a topic of much interest. Here, we describe two sequential reaching tasks that we use to investigate the neural substrate of skilled sequential movements in monkeys after long-term practice. The movement elements performed in these tasks are essentially identical, but are generated in two different contexts. In one task, monkeys perform reaching movements that are instructed by visual cues. In the other, the monkeys perform reaching movements that are generated from memory after extended practice. With this behavioral paradigm, we can dissociate the neural processes related to the acquisition and retention of motor skills from those related to movement execution.