Dynamics of motor direction representation in the primate premotor and primary motor cortices during sensorimotor learning

Ebina, T.; Sasagawa, A.; Hong, D.; Setsuie, R.; Obara, K.; Masamizu, Y.; Kondo, M.; Terada, S.-I.; Ozawa, K.; Uemura, M.; Takaji, M.; Watakabe, A.; Kobayashi, K.; Ohki, K.; Yamamori, T.; Murayama, M.; Matsuzaki, M.

doi:10.1101/2023.09.13.556461

bioRxiv · 10.1101/2023.09.13.556461

Dynamics of motor direction representation in the primate premotor and primary motor cortices during sensorimotor learning

Ebina, T.·Sasagawa, A.·Hong, D.·Setsuie, R.·Obara, K.·Masamizu, Y.·Kondo, M.·Terada, S.-I.·Ozawa, K.·Uemura, M.·Takaji, M.·Watakabe, A.·Kobayashi, K.·Ohki, K.·Yamamori, T.·Murayama, M.·Matsuzaki, M.

View original source ↗Export metadata ↓

Abstract

Sensorimotor learning requires reorganization of neuronal activity in the premotor cortex (PM) and primary motor cortex (M1). However, how PM- and M1-specific reorganization occurs in primates remains unclear. We conducted calcium imaging of these areas in common marmosets while they learned a two-target reaching (pull/push) task. Throughout learning, the dorsorostral PM (PMdr) showed peak activity earlier than the dorsocaudal PM (PMdc) and M1. PMdr showed decreased representation of newly introduced (push) movement, whereas PMdc and M1 maintained high representation. Many task-related neurons in PMdc and M1 exhibited a strong preference to either movement direction. PMdc neurons dynamically switched their preferred direction, whereas M1 neurons stably retained their preferred direction. Differences in preferred direction between adjacent neurons in PMdc increased during learning. These results suggest that in primate sensorimotor learning, dynamic motor representation in PMdc converts the cognitive sensorimotor signals of PMdr to stable and specific motor representation of M1.

Explore related subjects

neuroscience Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Ebina, T., Sasagawa, A., Hong, D., Setsuie, R., Obara, K., Masamizu, Y., Kondo, M., Terada, S.-I., Ozawa, K., Uemura, M., Takaji, M., Watakabe, A., Kobayashi, K., Ohki, K., Yamamori, T., Murayama, M., Matsuzaki, M.. 2023-09-14. Dynamics of motor direction representation in the primate premotor and primary motor cortices during sensorimotor learning. https://doi.org/10.1101/2023.09.13.556461

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Rab10 and Arhgef7 interact to promote axon extension by linking vesicle supply and exocytosis

The formation of functional neural circuits begins with the extension of a single axon by immature neurons. Axon elongation requires an expansion of the plasma membrane that depends on the polarization of vesicle trafficking and exocytosis. It is not completely understood how the increased transport of vesicles into the growing axon is linked to their subsequent insertion into the plasma membrane. An analysis of early stages of neuronal differentiation indicates that an asymmetry in neurite length precedes axon specification and the accumulation of PPVs in the nascent axon. We show that increasing the transport of vesicles in unpolarized neurons is sufficient to promote the extension of additional axons. This effect indicates that an increased supply of vesicles stimulates their subsequent insertion into the membrane to allow neurite growth. The link between vesicle transport and exocytosis is mediated by the interaction of Rab10 with Arhgef7. Rab10 stimulates Arhgef7 activity on PPVs as a GEF for Cdc42b to promote axon extension through exocyst-dependent exocytosis, suggesting that their interaction links the increased supply of PPVs to their exocytosis.

neuroscience↗

bioRxiv2026

Subcellular Spatial Profiling Unveils Links Between Neuritic Plaques with Selective Tau Vulnerability in Alzheimer's Disease

Alzheimer's disease (AD) features widespread extracellular amyloid-{beta} plaques but selective intraneuronal tau accumulation in cortical layers II/III and V, while layer IV remains relatively resistant. Here, we combined subcellular spatial transcriptomics with co-registered A{beta} and pTau immunohistochemistry to determine why neurons exposed to comparable plaque-associated pathology differ in somatic pTau accumulation. Plaque-associated neuritic stress occurred similarly across layers, but layer IV neurons showed attenuated pTau accumulation and reduced somatic expression of a shared neurite-soma stress program involving DCTN1, CALM3, NORAD, and PIN1. Trajectory analysis within layers identified tau-vulnerable and resistant neuronal states implicating calcium signaling, retrograde transport, and lysosomal function. Notably, astrocytic APOE-neuronal LRP1 co-expression increased significantly along the pTau-vulnerable trajectory, and APOE {epsilon}4 was associated with stronger coupling of local plaque pathology to pTau-associated molecular programs. These findings reveal neuronal programs and neuron-glia interactions underlying selective tau vulnerability and resistance in AD, highlighting potential tau-targeting therapeutics.

neuroscience↗

bioRxiv2026

Widespread oscillatory suppression in autism persists in the absence of psychotropic medication.

Purpose: Investigate the neural oscillatory activity associated with autism spectrum disorder (ASD) using electroencephalographic (EEG) recordings in children and adolescents. Compare the corresponding oscillatory power between ASD patients taking psychotropic medication with a drug-naive group. Methods: ASD diagnosis was done using DSM-IV and CARS (Childhood Autism Rating Scale). EEG recordings employed 22 scalp electrodes (10/20 system). ASD vs. neurotypical groups were matched for sex and age (5 females; average age: ~10 years old). We analyzed the resting state (eyes open) EEG power spectrum during ~2-minute recordings. The multitaper FFT method was used to estimate spectral power for the delta, theta, alpha, beta and gamma frequency bands. We pooled together data from several electrodes to compute comprehensive power spectra and assess the oscillatory behavior of macro brain regions. Results: We observed widespread (~4Hz - 20Hz) oscillatory suppression comprising the theta, alpha and beta frequency bands. The most widespread and robust ASD-associated power suppression was in the high theta and alpha bands. Delta and gamma bands showed no significant power change for any of the brain regions studied. Results from a subgroup of patients (N = 9) who never used psychotropics confirmed these findings, indicating that they are not an artifact of medication. Conclusion: Suppression in theta, alpha and beta oscillations may offer insights into the neurophysiological underpinnings of autism and could be used as an accessible and comprehensive tool in ASD diagnosis, regardless of the patients being or not on medication.

neuroscience↗