中枢神経系疾患の治療は正常細胞（ニューロン）の機能維持を目的とするが，脳血管障害のように機能障害の原因が細胞の死滅に基づくことは多い．一方，脳腫瘍の治療においては薬物療法や放射線療法といった腫瘍細胞の死滅を目標とするものが大きな位置を占める．いずれの場合にも，細胞死の機序を理解することは各種病態や治療法の理解のうえで重要である．現在のところ最も研究の進んでいる細胞死の型はアポトーシスである．そのなかで重要な位置を占めるミトコンドリアにおける反応および抗アポトーシス因子について概要を紹介する．

Neuroscience 細胞死：最近の知見

Noise — random disturbances of signals — poses a fundamental problem for information processing and affects all aspects of nervous-system function. However, the nature, amount and impact of noise in the nervous system have only recently been addressed in a quantitative manner. Experimental and computational methods have shown that multiple noise sources contribute to cellular and behavioural trial-to-trial variability. We review the sources of noise in the nervous system, from the molecular to the behavioural level, and show how noise contributes to trial-to-trial variability. We highlight how noise affects neuronal networks and the principles the nervous system applies to counter detrimental effects of noise, and briefly discuss noise's potential benefits.

/pdf/noise-in-the-nervous-system-22k10mncs2.pdf

Noise in the nervous system.

Immersive virtual environments can break the deep, everyday connection between where our senses tell us we are and where we are actually located and whom we are with. The concept of 'presence' refers to the phenomenon of behaving and feeling as if we are in the virtual world created by computer displays. In this article, we argue that presence is worthy of study by neuroscientists, and that it might aid the study of perception and consciousness.

/pdf/from-presence-to-consciousness-through-virtual-reality-3c3tfypz7n.pdf

From presence to consciousness through virtual reality

https://www.cell.com/trends/cognitive-sciences/pdf/S1364-6613(06)00127-6.pdf

Bayesian decision theory in sensorimotor control.

Deep learning in spiking neural networks

When planning target-directed reaching movements, human subjects combine visual and proprioceptive feedback to form two estimates of the arm's position: one to plan the reach direction, and another to convert that direction into a motor command. These position estimates are based on the same sensory signals but rely on different combinations of visual and proprioceptive input, suggesting that the brain weights sensory inputs differently depending on the computation being performed. Here we show that the relative weighting of vision and proprioception depends both on the sensory modality of the target and on the information content of the visual feedback, and that these factors affect the two stages of planning independently. The observed diversity of weightings demonstrates the flexibility of sensory integration and suggests a unifying principle by which the brain chooses sensory inputs so as to minimize errors arising from the transformation of sensory signals between coordinate frames.

/pdf/flexible-strategies-for-sensory-integration-during-motor-564ywssuwf.pdf

Flexible strategies for sensory integration during motor planning

When planning goal-directed reaches, subjects must estimate the position of the arm by integrating visual and proprioceptive signals from the sensory periphery. These integrated position estimates are required at two stages of motor planning: first to determine the desired movement vector, and second to transform the movement vector into a joint-based motor command. We quantified the contributions of each sensory modality to the position estimate formed at each planning stage. Subjects made reaches in a virtual reality environment in which vision and proprioception were dissociated by shifting the location of visual feedback. The relative weighting of vision and proprioception at each stage was then determined using computational models of feedforward motor control. We found that the position estimate used for movement vector planning relies mostly on visual input, whereas the estimate used to compute the joint-based motor command relies more on proprioceptive signals. This suggests that when estimating the position of the arm, the brain selects different combinations of sensory input based on the computation in which the resulting estimate will be used.

https://www.jneurosci.org/content/jneuro/23/18/6982.full.pdf

Multisensory Integration during Motor Planning

Birdsong is a learned behavior remarkable for its high degree of stereotypy. Nevertheless, adult birds display substantial rendition-by-rendition variation in the structure of individual song elements or "syllables." Previous work suggests that some of this variation is actively generated by the avian basal ganglia circuitry for purposes of motor exploration. However, it is unknown whether and how natural variations in premotor activity drive variations in syllable structure. Here, we recorded from the premotor nucleus robust nucleus of the arcopallium (RA) in Bengalese finches and measured whether neural activity covaried with syllable structure across multiple renditions of individual syllables. We found that variations in premotor activity were significantly correlated with variations in the acoustic features (pitch, amplitude, and spectral entropy) of syllables in approximately a quarter of all cases. In these cases, individual neural recordings predicted 8.5 +/- 0.3% (mean +/- SE) of the behavioral variation, and in some cases accounted for 25% or more of trial-by-trial variations in acoustic output. The prevalence and strength of neuron-behavior correlations indicate that each acoustic feature is controlled by a large ensemble of neurons that vary their activity in a coordinated manner. Additionally, we found that correlations with pitch (but not other features) were predominantly positive in sign, supporting a model of pitch production based on the anatomy and physiology of the vocal motor apparatus. Collectively, our results indicate that trial-by-trial variations in spectral structure are indeed under central neural control at the level of RA, consistent with the idea that such variation reflects motor exploration.

https://www.jneurosci.org/content/jneuro/28/41/10370.full.pdf

Central Contributions to Acoustic Variation in Birdsong

Humans learn to speak by a process of vocal imitation that requires the availability of auditory feedback. Similarly, young birds rely on auditory feedback when learning to imitate the songs of adult birds, providing one of the few examples of nonhuman vocal learning. However, although humans continue to use auditory feedback to correct vocal errors in adulthood, the mechanisms underlying the stability of adult birdsong are unknown. We found that, similar to human speech, adult birdsong is maintained by error correction. We perturbed the pitch (fundamental frequency) of auditory feedback in adult Bengalese finches using custom-designed headphones. Birds compensated for the imposed auditory error by adjusting the pitch of song. When the perturbation was removed, pitch returned to baseline. Our results indicate that adult birds correct vocal errors by comparing auditory feedback to a sensory target and suggest that lifelong error correction is a general principle of learned vocal behavior.

/pdf/adult-birdsong-is-actively-maintained-by-error-correction-u3lhns1y2k.pdf

Adult birdsong is actively maintained by error correction.

As animals vocalize, their vocal organ transforms motor commands into vocalizations for social communication. In birds, the physical mechanisms by which vocalizations are produced and controlled remain unresolved because of the extreme difficulty in obtaining in vivo measurements. Here, we introduce an ex vivo preparation of the avian vocal organ that allows simultaneous high-speed imaging, muscle stimulation and kinematic and acoustic analyses to reveal the mechanisms of vocal production in birds across a wide range of taxa. Remarkably, we show that all species tested employ the myoelastic-aerodynamic (MEAD) mechanism, the same mechanism used to produce human speech. Furthermore, we show substantial redundancy in the control of key vocal parameters ex vivo, suggesting that in vivo vocalizations may also not be specified by unique motor commands. We propose that such motor redundancy can aid vocal learning and is common to MEAD sound production across birds and mammals, including humans.

/pdf/universal-mechanisms-of-sound-production-and-control-in-3rpt54es9n.pdf

Samuel J. Sober

Papers

Flexible strategies for sensory integration during motor planning

Multisensory Integration during Motor Planning

Central Contributions to Acoustic Variation in Birdsong

Adult birdsong is actively maintained by error correction.

Universal mechanisms of sound production and control in birds and mammals