Top-Down Control of Motor Cortex Ensembles by Dorsomedial Prefrontal Cortex

SummaryDorsomedial prefrontal cortex is critical for the temporal control of behavior. Dorsomedial prefrontal cortex might alter neuronal activity in areas such as motor cortex to inhibit temporally inappropriate responses. We tested this hypothesis by recording from neuronal ensembles in rodent dorsomedial prefrontal cortex during a delayed-response task. One-third of dorsomedial prefrontal neurons were significantly modulated during the delay period. The activity of many of these neurons was predictive of premature responding. We then reversibly inactivated dorsomedial prefrontal cortex while recording ensemble activity in motor cortex. Inactivation of dorsomedial prefrontal cortex reduced delay-related firing, but not response-related firing, in motor cortex. Finally, we made simultaneous recordings in dorsomedial prefrontal cortex and motor cortex and found strong delay-related temporal correlations between neurons in the two cortical areas. These data suggest that functional interactions between dorsomedial prefrontal cortex and motor cortex might serve as a top-down control signal that inhibits inappropriate responding

[2-(4-Methylbenzoyl)phenyl](4-methylphenyl)methanone

The asymmetric unit of the title compound, C22H18O2, contains one half-mol­ecule, the complete mol­ecule being generated by the operation of a crystallographic twofold rotation axis. The carbonyl group and the two C atoms attached to it forms inter­planar angles of 23.67 (7)° with the methyl-substituted phenyl ring and 50.74 (8)° with the central ring. In the crystal, mol­ecules are linked into infinite chains along the b-axis direction by inter­molecular C—H⋯O inter­actions, generating R 2 2(10) graph-set motifs

Effect of deep brain stimulation on vocal motor control mechanisms in Parkinson's disease

Published online: March 07, 2019motor symptoms in Parkinson's disease (PD); however, its effect on vocal motor function has yielded conflicted and highly variable results. The present study investigated the effects of STN-DBS on the mechanisms of vocal production and motor control. Methods: A total of 10 PD subjects with bilateral STN-DBS implantation were tested with DBS ON and OFF while they performed steady vowel vocalizations and received randomized upward or downward pitch-shift stimuli (±100 cents) in their voice auditory feedback. Results: Data showed that the magnitude of vocal compensation responses to pitch-shift stimuli was significantly attenuated during DBS ON vs. OFF (p = 0.012). This effect was direction-specific and was only observed when subjects raised their voice fundamental frequency (F0) in the opposite direction to downward stimuli (p = 0.019). In addition, we found that voice F0 perturbation (i.e. jitter) was significantly reduced during DBS ON vs. OFF (p = 0.022), and this DBS-induced modulation was positively correlated with the attenuation of vocal compensation responses to downward pitch-shift stimuli (r = +0.57, p = 0.028). Conclusions: These findings provide the first data supporting the role of STN in vocal F0 motor control in response to altered auditory feedback. The DBS-induced attenuation of vocal compensation responses may result from increased inhibitory effects of the subcortical hyperdirect (fronto-subthalamic) pathways on the vocal motor cortex, which can help stabilize voice F0 and ameliorate vocal motor symptoms by impeding PD subjects’ abnormal (i.e. overshooting) vocal responses to alterations in the auditory feedback

[3-Hy­droxy­methyl-1,4-bis­(4-methyl­phen­yl)naphthalen-2-yl]methanol

In the title compound, C26H24O2, the crowded naphthalene ring system is essentially planar [maximum deviation of 0.027 (2) Å for one of the C atoms of the unsubstituted ring]. In the crystal, mol­ecules are connected by O—H⋯O hydrogen bonds into chains along the a axis. Pairs of the oppositely oriented chains are further cross-linked by O—H⋯O hydrogen bonds, forming infinte bands of alternating R 4 4(8) dimers and R 2 2(14) motifs

Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators

Analog in-memory computing (AIMC) -- a promising approach for energy-efficient acceleration of deep learning workloads -- computes matrix-vector multiplications (MVMs) but only approximately, due to nonidealities that often are non-deterministic or nonlinear. This can adversely impact the achievable deep neural network (DNN) inference accuracy as compared to a conventional floating point (FP) implementation. While retraining has previously been suggested to improve robustness, prior work has explored only a few DNN topologies, using disparate and overly simplified AIMC hardware models. Here, we use hardware-aware (HWA) training to systematically examine the accuracy of AIMC for multiple common artificial intelligence (AI) workloads across multiple DNN topologies, and investigate sensitivity and robustness to a broad set of nonidealities. By introducing a new and highly realistic AIMC crossbar-model, we improve significantly on earlier retraining approaches. We show that many large-scale DNNs of various topologies, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers, can in fact be successfully retrained to show iso-accuracy on AIMC. Our results further suggest that AIMC nonidealities that add noise to the inputs or outputs, not the weights, have the largest impact on DNN accuracy, and that RNNs are particularly robust to all nonidealities.Comment: 35 pages, 7 figures, 5 table

Capacity-Speed Relationships in Prefrontal Cortex

Working memory (WM) capacity and WM processing speed are simple cognitive measures that underlie human performance in complex processes such as reasoning and language comprehension. These cognitive measures have shown to be interrelated in behavioral studies, yet the neural mechanism behind this interdependence has not been elucidated. We have carried out two functional MRI studies to separately identify brain regions involved in capacity and speed. Experiment 1, using a block-design WM verbal task, identified increased WM capacity with increased activity in right prefrontal regions, and Experiment 2, using a single-trial WM verbal task, identified increased WM processing speed with increased activity in similar regions. Our results suggest that right prefrontal areas may be a common region interlinking these two cognitive measures. Moreover, an overlap analysis with regions associated with binding or chunking suggest that this strategic memory consolidation process may be the mechanism interlinking WM capacity and WM speed.National Center for Research Resources (U.S.) (grant UL1RR025011)National Institutes of Health (U.S.) (grant NIH RO1 DC05375)Wallace H. Coulter FoundationNational Institute of Mental Health (U.S.) (Challenge Grant RC1MH090912-01

Enhancing glycolysis attenuates Parkinson's disease progression in models and clinical databases

Parkinson's disease (PD) is a common neurodegenerative disease that lacks therapies to prevent progressive neurodegeneration. Impaired energy metabolism and reduced ATP levels are common features of PD. Previous studies revealed that terazosin (TZ) enhances the activity of phosphoglycerate kinase 1 (PGK1), thereby stimulating glycolysis and increasing cellular ATP levels. Therefore, we asked whether enhancement of PGK1 activity would change the course of PD. In toxin-induced and genetic PD models in mice, rats, flies, and induced pluripotent stem cells, TZ increased brain ATP levels and slowed or prevented neuron loss. The drug increased dopamine levels and partially restored motor function. Because TZ is prescribed clinically, we also interrogated 2 distinct human databases. We found slower disease progression, decreased PD-related complications, and a reduced frequency of PD diagnoses in individuals taking TZ and related drugs. These findings suggest that enhancing PGK1 activity and increasing glycolysis may slow neurodegeneration in PD