
「引き寄せの法則」を効果的に活用するには、自分自身と人生に対する信頼を持つことが重要である。


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The Uncomfortable Truth About Why The Law of Attraction Doesn’t Work for You

なぜ-引き寄せの法則-があなたに効果がないのかについての真実


なぜ「引き寄せの法則」があなたに効果がないのかについての真実


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実践を通して学ぶことの重要性


After 10 Years of Experimenting With the Law of Attraction, Here Are The 4 Most Valuable Lessons…

10年間の引力の法則の実験から学んだ4つの最も価値のある教訓


慢性的な神経活動記録のために、再利用可能で軽量で柔軟な「アポロインプラント」を開発した。このインプラントは、自由行動下のマウスやラットでの長期にわたる安定した神経活動記録を可能にする。


Electrophysiology has proven invaluable to record neural activity, and the development of Neuropixels probes dramatically increased the number of recorded neurons. These probes are often implanted acutely, but acute recordings cannot be performed in freely moving animals and the recorded neurons cannot be tracked across days. To study key behaviors such as navigation, learning, and memory formation, the probes must be implanted chronically. An ideal chronic implant should (1) allow stable recordings of neurons for weeks; (2) allow reuse of the probes after explantation; (3) be light enough for use in mice. Here, we present the “Apollo Implant”, an open-source and editable device that meets these criteria and accommodates up to two Neuropixels 1.0 or 2.0 probes. The implant comprises a “payload” module which is attached to the probe and is recoverable, and a “docking” module which is cemented to the skull. The design is adjustable, making it easy to change the distance between probes, the angle of insertion, and the depth of insertion. We tested the implant across eight labs in head-fixed mice, freely moving mice, and freely moving rats. The number of neurons recorded across days was stable, even after repeated implantations of the same probe. The Apollo implant provides an inexpensive, lightweight, and flexible solution for reusable chronic Neuropixels recordings.

### Competing Interest Statement

The authors have declared no competing interest.

An adaptable, reusable, and light implant for chronic Neuropixels probes

神経ピクセルプローブ用の再利用可能で柔軟で軽量な慢性インプラントの開発


本研究では、自己相関アプローチに基づく新しい「サイクル均一振動(CHO)検出法」を提案し、非正弦波ニューロン振動の検出精度と特異性を大幅に向上させた。


Detecting temporal and spectral features of neural oscillations is essential to understanding dynamic brain function. Traditionally, the presence and frequency of neural oscillations are determined by identifying peaks over 1/f noise within the power spectrum. However, this approach solely operates within the frequency domain and thus cannot adequately distinguish between the fundamental frequency of a non-sinusoidal oscillation and its harmonics. Non-sinusoidal signals generate harmonics, significantly increasing the false-positive detection rate — a confounding factor in the analysis of neural oscillations. To overcome these limitations, we define the fundamental criteria that characterize a neural oscillation and introduce the Cyclic Homogeneous Oscillation (CHO) detection method that implements these criteria based on an auto-correlation approach that determines the oscillation’s periodicity and fundamental frequency. We evaluated CHO by verifying its performance on simulated sinusoidal and non-sinusoidal oscillatory bursts convolved with 1/f noise. Our results demonstrate that CHO outperforms conventional techniques in accurately detecting oscillations. Specifically, we determined the sensitivity and specificity of CHO as a function of signal-to-noise ratio (SNR). We further assessed CHO by testing it on electrocorticographic (ECoG, 8 subjects) and electroencephalographic (EEG, 7 subjects) signals recorded during the pre-stimulus period of an auditory reaction time task and on electrocorticographic signals (6 SEEG subjects and 6 ECoG subjects) collected during resting state. In the reaction time task, the CHO method detected auditory alpha and pre-motor beta oscillations in ECoG signals and occipital alpha and pre-motor beta oscillations in EEG signals. Moreover, CHO determined the fundamental frequency of hippocampal oscillations in the human hippocampus during the resting state (6 SEEG subjects). In summary, CHO demonstrates high precision and specificity in detecting neural oscillations in time and frequency domains. The method’s specificity enables the detailed study of non-sinusoidal characteristics of oscillations, such as the degree of asymmetry and waveform of an oscillation. Furthermore, CHO can be applied to identify how neural oscillations govern interactions throughout the brain and to determine oscillatory biomarkers that index abnormal brain function.

### Competing Interest Statement

One U.S. patent (Provisional Application Serial No.63/326,257) related to systems and methods for the detection of neurophysiological signal oscillations described in this manuscript was filed on March 31, 2022. The inventors/contributors of this patent involve some of the manuscript authors, including HC, MA, JTW, and PB.

Datasets may be provided to interested researchers upon reasonable request to the corresponding author.

Novel Cyclic Homogeneous Oscillation Detection Method for High Accuracy and Specific Characterization of Neural Dynamics

非正弦波ニューロン振動の高精度検出と特徴付けのための新規サイクル均一振動検出法


感覚入力に対する適切な行動反応を生み出すには、課題規則に応じた皮質領域の事前状態の設定が重要である。


Flexible responses to sensory stimuli based on changing rules are critical for adapting to a dynamic environment. However, it remains unclear how the brain encodes rule information and uses this information to guide behavioral responses to sensory stimuli. Here, we made single-unit recordings while head-fixed mice performed a cross-modal sensory selection task in which they switched between two rules in different blocks of trials: licking in response to tactile stimuli applied to a whisker while rejecting visual stimuli, or licking to visual stimuli while rejecting the tactile stimuli. Along a cortical sensorimotor processing stream including the primary (S1) and secondary (S2) somatosensory areas, and the medial (MM) and anterolateral (ALM) motor areas, the single-trial activity of individual neurons distinguished between the two rules both prior to and in response to the tactile stimulus. Variable rule-dependent responses to identical stimuli could in principle occur via appropriate configuration of pre-stimulus preparatory states of a neural population, which would shape the subsequent response. We hypothesized that neural populations in S1, S2, MM and ALM would show preparatory activity states that were set in a rule-dependent manner to cause processing of sensory information according to the current rule. This hypothesis was supported for the motor cortical areas by findings that (1) the current task rule could be decoded from pre-stimulus population activity in ALM and MM; (2) neural subspaces containing the population activity differed between the two rules; and (3) optogenetic disruption of pre-stimulus states within ALM and MM impaired task performance. Our findings indicate that flexible selection of an appropriate action in response to a sensory input can occur via configuration of preparatory states in the motor cortex.

HIGHLIGHTS 

### Competing Interest Statement

The authors have declared no competing interest.

Rule-based modulation of a sensorimotor transformation across cortical areas

感覚運動変換の規則に基づく皮質領域間の調節