Insights into motor learning from a viewpoint of transcranial magnetic stimulation

Several protocols of non-invasive transcranial magnetic stimulation have been developed in the past decades. Single-and paired-pulse transcranial magnetic stimulation are painless, and noninvasive tools to evaluate cortical and corticospinal excitability in cerebral cortex compared with transcranial electric stimulation. Motor evoked potential induced by paired-pulse transcranial magnetic stimulation can particularly assess changes of the cortical excitability after motor learning, such as motor skill and motor practice in sports and functional recovery in rehabilitation. However, the effect of electric current in transcranial magnetic stimulation on pyramidal neuron and interneuron in gray and white matters is not actually understood well yet in the field of sports and rehabilitation sciences. Here, we show the important basic knowledge of neurophysiology and transcranial magnetic stimulation and introduce some studies of cortical plasticity and motor learning by using transcranial magnetic stimulation

Echoic memory of a single pure tone indexed by change-related brain activity

<p>Abstract</p> <p>Background</p> <p>The rapid detection of sensory change is important to survival. The process should relate closely to memory since it requires that the brain separate a new stimulus from an ongoing background or past event. Given that sensory memory monitors current sensory status and works to pick-up changes in real-time, any change detected by this system should evoke a change-related cortical response. To test this hypothesis, we examined whether the single presentation of a sound is enough to elicit a change-related cortical response, and therefore, shape a memory trace enough to separate a subsequent stimulus.</p> <p>Results</p> <p>Under a paradigm where two pure sounds 300 ms in duration and 800 or 840 Hz in frequency were presented in a specific order at an even probability, cortical responses to each sound were measured with magnetoencephalograms. Sounds were grouped to five events regardless of their frequency, 1D, 2D, and 3D (a sound preceded by one, two, or three different sounds), and 1S and 2S (a sound preceded by one or two same sounds). Whereas activation in the planum temporale did not differ among events, activation in the superior temporal gyrus (STG) was clearly greater for the different events (1D, 2D, 3D) than the same event (1S and 2S).</p> <p>Conclusions</p> <p>One presentation of a sound is enough to shape a memory trace for comparison with a subsequent physically different sound and elicits change-related cortical responses in the STG. The STG works as a real-time sensory gate open to a new event.</p

The effect of water immersion on short-latency somatosensory evoked potentials in human

<p>Abstract</p> <p>Background</p> <p>Water immersion therapy is used to treat a variety of cardiovascular, respiratory, and orthopedic conditions. It can also benefit some neurological patients, although little is known about the effects of water immersion on neural activity, including somatosensory processing. To this end, we examined the effect of water immersion on short-latency somatosensory evoked potentials (SEPs) elicited by median nerve stimuli. Short-latency SEP recordings were obtained for ten healthy male volunteers at rest in or out of water at 30°C. Recordings were obtained from nine scalp electrodes according to the 10-20 system. The right median nerve at the wrist was electrically stimulated with the stimulus duration of 0.2 ms at 3 Hz. The intensity of the stimulus was fixed at approximately three times the sensory threshold.</p> <p>Results</p> <p>Water immersion significantly reduced the amplitudes of the short-latency SEP components P25 and P45 measured from electrodes over the parietal region and the P45 measured by central region.</p> <p>Conclusions</p> <p>Water immersion reduced short-latency SEP components known to originate in several cortical areas. Attenuation of short-latency SEPs suggests that water immersion influences the cortical processing of somatosensory inputs. Modulation of cortical processing may contribute to the beneficial effects of aquatic therapy.</p> <p>Trial Registration</p> <p>UMIN-CTR (UMIN000006492)</p

Non-linear laws of echoic memory and auditory change detection in humans

<p>Abstract</p> <p>Background</p> <p>The detection of any abrupt change in the environment is important to survival. Since memory of preceding sensory conditions is necessary for detecting changes, such a change-detection system relates closely to the memory system. Here we used an auditory change-related N1 subcomponent (change-N1) of event-related brain potentials to investigate cortical mechanisms underlying change detection and echoic memory.</p> <p>Results</p> <p>Change-N1 was elicited by a simple paradigm with two tones, a standard followed by a deviant, while subjects watched a silent movie. The amplitude of change-N1 elicited by a fixed sound pressure deviance (70 dB vs. 75 dB) was negatively correlated with the logarithm of the interval between the standard sound and deviant sound (1, 10, 100, or 1000 ms), while positively correlated with the logarithm of the duration of the standard sound (25, 100, 500, or 1000 ms). The amplitude of change-N1 elicited by a deviance in sound pressure, sound frequency, and sound location was correlated with the logarithm of the magnitude of physical differences between the standard and deviant sounds.</p> <p>Conclusions</p> <p>The present findings suggest that temporal representation of echoic memory is non-linear and Weber-Fechner law holds for the automatic cortical response to sound changes within a suprathreshold range. Since the present results show that the behavior of echoic memory can be understood through change-N1, change-N1 would be a useful tool to investigate memory systems.</p

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Somatosensory and auditory change detection system in humans

　ヒトが生存していくためには感覚系に発生したあらゆる変化を素早く察知し、その変化に注意を向け、発生事象の詳細を吟味し、適切な行動へのドライブを発生させる脳内ネットワークが必要不可欠である。そして、このネットワークの最重要部分は個体の意識を必要としない自動処理であると推察される。近年、機能的磁気共鳴画像法（fMRI、以下fMRI）を用いた研究により、各感覚系において変化に対して活動する脳部位が報告されている。しかしながら、変化に対する脳活動の時間的動態についてはいまだに明らかにされていない。　彼らの研究室では、優れた時間分解能を有する脳波・脳磁図を用いてヒトの感覚情報処理機構について精力的に研究を行ってきた。その結果、ヒトの感覚情報処理は各感覚系に共通して刺激後約20～30msでピークを迎える初期活動と刺激後約100ms程度でピークを迎える後期活動にわけられることを明らかにした。さらに、初期活動の振幅は刺激頻度の変化にほとんど影響を受けない一方で、後期活動の振幅は刺激頻度が増すと減少し、刺激頻度が減ると増大することを確認した。これらの結果は、後期活動が初期活動のように刺激に対して1対1で反応するような単純な情報処理過程ではなく、より複雑な認知的過程を反映している可能性を示唆している。そこで、彼らは「後期活動は変化に対する自動応答である」との仮説を立てた。そして、後期活動が変化に対する自動応答だとすると後期活動は文字通りの刺激の変化のみならず突然の刺激の呈示（ON、以下ON）あるいは刺激の消失（OFF、以下OFF）に対しても誘発されるはずである。この仮説を証明するために脳波・脳磁図を用いて実験を行った。　第1実験として、刺激のパラメーターを容易に変えることができる体性感覚をターゲットに実験を行った。刺激には一定時間持続（1～3s）する3種類の刺激内間隔時間（ISI、以下ISI）10、20、50msに設定したトレイン電気刺激を用いた。刺激は右手手背に呈示し、その刺激のONとOFFにトリガーをかけ脳波を記録した。実験は後期活動が変化に対する自動応答として誘発されるという仮説を証明するために、刺激に注意を向ける条件とビデオに集中してもらい刺激に注意を向けない条件でそれぞれ行った。結果、注意・非注意時に関わらずON・OFF刺激に共通して刺激後100ms付近に陽性と陰性の脳活動（P100・N140）が誘発された。刺激が一定時間呈示され続けているにも関わらずP100・N140は刺激のON・OFF時にのみ誘発され（同じ刺激の連続は変化として検出されない）、さらに物理的な刺激が存在しない場合（OFF）にも誘発されることから、これらの反応が刺激自体に対する脳活動ではなく変化に対する脳活動を反映していることが示唆された。さらに、ON反応におけるP100・N140は3種類のISI条件で潜時が綺麗に揃っていたのに対して、OFF反応におけるP100・N140の潜時はISIに依存して延長していた。つまり、ISI50msの刺激の場合は50msごとに刺激が呈示されており、この刺激パターンを脳が記憶している。したがって、OFF反応においては次の刺激がこないことを脳が変化として検出できるのは刺激が終わってから約50ms経過してからである。その結果、刺激の実際のOFFポイントでなく、そのポイントから約50ms遅れてP100・N140が誘発されたと推察される。これらの結果から、後期活動は短期記憶により保持された変化前の事象と最新の事象との比較により誘発される皮質の自動応答であることが示唆された。　実験2では、後期活動の信号源について検討するために脳波より優れた空間分解能を有する脳磁図を用いて実験を行った。刺激は実験1と同様にトレイン電気刺激（ISI20ms）を用いて、刺激のONとOFFにトリガーをかけた。本実験においても被験者にはビデオを見てもらい、刺激を無視するように教示した。結果、実験1と同様にON・OFF刺激に共通して刺激後100ms付近に脳活動（P100m）が誘発された。この活動の信号源はON・OFF刺激に共通して第二次体性感覚野付近に推定された。先行研究において、第二次体性感覚野は体性感覚に起こった変化に対して活動する脳部位として報告されており、彼らの結果はこの報告とも一致した。これらの結果から、後期活動は主に高次感覚野の活動により構成されることが示唆された。　先行研究において各感覚系に共通する初期活動・後期活動が誘発されたことから、実験3では、聴覚においても後期活動が変化に対する自動応答を担っているかどうかを検討することを目的とした。実験は1000Hz純音の継続音と1000Hz純音によって構成される2種類のトレイン音（ISI:50、100ms）を用いて行った。本実験においても被験者にはビデオを見てもらい、刺激を無視するように教示した。結果、聴覚においてもON・OFF刺激に共通する100ms付近の脳活動（N1m、以下N1m）が誘発され、ON反応におけるN1mの潜時は3つのISI条件で綺麗に揃っていたのに対して、OFF反応におけるN1mの潜時は体性感覚実験と同様にISIに依存して延長していた。また、この活動の信号源はON・OFF刺激に共通して左右の上側頭回付近に推定された。先行研究において、上側頭回は聴覚に起こった変化に対して活動する脳部位として報告されている。これらの結果から、聴覚においても後期活動は主に高次感覚野の活動により構成され、変化に対する自動応答を反映する脳活動であることが示唆された。　以上、変化検出機構（後期活動）は短期記憶により保持された変化前の事象と最新の事象との比較により自動的に駆動され、その活動の責任部位は各感覚野の高次領域であることが示唆された

Menstrual Cycle Modulates Motor Learning and Memory Consolidation in Humans

Numerous studies have noted that sex and/or menstrual phase influences cognitive performance (in particular, declarative memory), but the effects on motor learning (ML) and procedural memory/consolidation remain unclear. In order to test the hypothesis that ML differs across menstrual cycle phases, initial ML, overlearning, consolidation, and final performance were assessed in women in the follicular, preovulation and luteal phases. Primary motor cortex (M1) oscillations were assessed neuro-physiologically, and premenstrual syndrome and interoceptive awareness scores were assessed psychologically. We found not only poorer performance gain through initial ML but also lower final performance after overlearning a day and a week later in the luteal group than in the ovulation group. This behavioral difference could be explained by particular premenstrual syndrome symptoms and associated failure of normal M1 excitability in the luteal group. In contrast, the offline effects, i.e., early and late consolidation, did not differ across menstrual cycle phases. These results provide information regarding the best time in which to start learning new sensorimotor skills to achieve expected gains

Action Postponing and Restraint Varies among Sensory Modalities

Proactive inhibition is divided into two components: action postponing (AP), which refers to slowing the onset of response, and action restraint (AR), which refers to preventing the response. To date, several studies have reported alterations in proactive inhibition and its associated neural processing among sensory modalities; however, this remains inconclusive owing to several methodological issues. This study aimed to clarify the differences in AP and AR and their neural processing among visual, auditory, and somatosensory modalities using an appropriate experimental paradigm that can assess AP and AR separately. The postponing time calculated by subtracting simple reaction time from Go signal reaction time was shorter in the visual modality than in the other modalities. This was explained by faster neural processing for conflict monitoring induced by anticipating the presence of the No-go signal, supported by the shorter latency of AP-related N2. Furthermore, the percentage of false alarms, which is the reaction to No-go signals, was lower in the visual modality than in the auditory modality. This was attributed to higher neural resources for conflict monitoring induced by the presence of No-go signals, supported by the larger amplitudes of AR-related N2. Our findings revealed the differences in AP and AR and their neural processing among sensory modalities