Original speech and its echo are segregated and separately processed in the human brain.

Speech recognition crucially relies on slow temporal modulations (<16 Hz) in speech. Recent studies, however, have demonstrated that the long-delay echoes, which are common during online conferencing, can eliminate crucial temporal modulations in speech but do not affect speech intelligibility. Here, we investigated the underlying neural mechanisms. MEG experiments demonstrated that cortical activity can effectively track the temporal modulations eliminated by an echo, which cannot be fully explained by basic neural adaptation mechanisms. Furthermore, cortical responses to echoic speech can be better explained by a model that segregates speech from its echo than by a model that encodes echoic speech as a whole. The speech segregation effect was observed even when attention was diverted but would disappear when segregation cues, i.e., speech fine structure, were removed. These results strongly suggested that, through mechanisms such as stream segregation, the auditory system can build an echo-insensitive representation of speech envelope, which can support reliable speech recognition.

The RNA ligase RNA terminal phosphate cyclase B regulates mRNA alternative splicing and is required for mouse oocyte development and maintenance.

Recent large-scale mRNA sequencing has shown that introns are retained in 5-10% of mRNA, and these events are named intron retention (IR). IR has been recognized as a key mechanism in the regulation of gene expression. However, the role of this mechanism in female reproduction in mammals remains unclear. RNA terminal phosphate cyclase B (RTCB) is a RNA ligase; we found that RTCB conditional knockout mice have premature ovarian failure and that RTCB plays a crucial role in follicular development. RTCB regulated the splicing of transcripts related to DNA methylation and DNA damage repair. In addition, it regulated the resumption of oocyte meiosis by affecting CDK1 activation. Moreover, the loss of RTCB suppressed zygotic genome activation (ZGA) and decreased translation at the global level. In addition, Rtcb deletion resulted in the accumulation of maternal mRNAs containing unspliced introns and in a decline in the overall level of transcripts. As a result, the Rtcb-/- females were sterile. Our study highlights the important role of RTCB-regulated noncanonical alternative splicing in female reproduction.

Delta-band neural tracking primarily reflects rule-based chunking instead of semantic relatedness between words.

It is debated whether cortical responses matching the time scales of phrases and sentences mediate the mental construction of the syntactic chunks or are simply caused by the semantic properties of words. Here, we investigate to what extent delta-band neural responses to speech can be explained by semantic relatedness between words. To dissociate the contribution of semantic relatedness from sentential structures, participants listened to sentence sequences and paired-word sequences in which semantically related words repeated at 1 Hz. Semantic relatedness in the 2 types of sequences was quantified using a word2vec model that captured the semantic relation between words without considering sentential structure. The word2vec model predicted comparable 1-Hz responses with paired-word sequences and sentence sequences. However, empirical neural activity, recorded using magnetoencephalography, showed a weaker 1-Hz response to paired-word sequences than sentence sequences in a word-level task that did not require sentential processing. Furthermore, when listeners applied a task-related rule to parse paired-word sequences into multi-word chunks, 1-Hz response was stronger than that in word-level task on the same sequences. Our results suggest that cortical activity tracks multi-word chunks constructed by either syntactic rules or task-related rules, whereas the semantic relatedness between words contributes only in a minor way.

The neural correlates of amplitude of low-frequency fluctuation: a multimodal resting-state MEG and fMRI-EEG study.

The amplitude of low-frequency fluctuation (ALFF) describes the regional intensity of spontaneous blood-oxygen-level-dependent signal in resting-state functional magnetic resonance imaging (fMRI). How the fMRI-ALFF relates to the amplitude in electrophysiological signals remains unclear. We here aimed to investigate the neural correlates of fMRI-ALFF by comparing the spatial difference of amplitude between the eyes-closed (EC) and eyes-open (EO) states from fMRI and magnetoencephalography (MEG), respectively. By synthesizing MEG signal into amplitude-based envelope time course, we first investigated 2 types of amplitude in MEG, meaning the amplitude of neural activities from delta to gamma (i.e. MEG-amplitude) and the amplitude of their low-frequency modulation at the fMRI range (i.e. MEG-ALFF). We observed that the MEG-ALFF in EC was increased at parietal sensors, ranging from alpha to beta; whereas the MEG-amplitude in EC was increased at the occipital sensors in alpha. Source-level analysis revealed that the increased MEG-ALFF in the sensorimotor cortex overlapped with the most reliable EC-EO differences observed in fMRI at slow-3 (0.073-0.198 Hz), and these differences were more significant after global mean standardization. Taken together, our results support that (i) the amplitude at 2 timescales in MEG reflect distinct physiological information and that (ii) the fMRI-ALFF may relate to the ALFF in neural activity.

Statistical learning in patients in the minimally conscious state.

When listening to speech, cortical activity can track mentally constructed linguistic units such as words, phrases, and sentences. Recent studies have also shown that the neural responses to mentally constructed linguistic units can predict the outcome of patients with disorders of consciousness (DoC). In healthy individuals, cortical tracking of linguistic units can be driven by both long-term linguistic knowledge and online learning of the transitional probability between syllables. Here, we investigated whether statistical learning could occur in patients in the minimally conscious state (MCS) and patients emerged from the MCS (EMCS) using electroencephalography (EEG). In Experiment 1, we presented to participants an isochronous sequence of syllables, which were composed of either 4 real disyllabic words or 4 reversed disyllabic words. An inter-trial phase coherence analysis revealed that the patient groups showed similar word tracking responses to real and reversed words. In Experiment 2, we presented trisyllabic artificial words that were defined by the transitional probability between words, and a significant word-rate EEG response was observed for MCS patients. These results suggested that statistical learning can occur with a minimal conscious level. The residual statistical learning ability in MCS patients could potentially be harnessed to induce neural plasticity.

Neural substrate underlying the learning of a passage with unfamiliar vocabulary and syntax.

Speech comprehension is a complex process involving multiple stages, such as decoding of phonetic units, recognizing words, and understanding sentences and passages. In this study, we identify cortical networks beyond basic phonetic processing using a novel passage learning paradigm. Participants learn to comprehend a story composed of syllables of their native language, but containing unfamiliar vocabulary and syntax. Three learning methods are employed, each resulting in some degree of learning within a 12-min learning session. Functional magnetic resonance imaging results reveal that, when listening to the same story, the classic temporal-frontal language network is significantly enhanced by learning. Critically, activation of the left anterior and posterior temporal lobe correlates with the learning outcome that is assessed behaviorally through, e.g. word recognition and passage comprehension tests. This study demonstrates that a brief learning session is sufficient to induce neural plasticity in the left temporal lobe, which underlies the transformation from phonetic units to the units of meaning, such as words and sentences.

The different brain areas occupied for integrating information of hierarchical linguistic units: a study based on EEG and TMS.

Human language units are hierarchical, and reading acquisition involves integrating multisensory information (typically from auditory and visual modalities) to access meaning. However, it is unclear how the brain processes and integrates language information at different linguistic units (words, phrases, and sentences) provided simultaneously in auditory and visual modalities. To address the issue, we presented participants with sequences of short Chinese sentences through auditory, visual, or combined audio-visual modalities while electroencephalographic responses were recorded. With a frequency tagging approach, we analyzed the neural representations of basic linguistic units (i.e. characters/monosyllabic words) and higher-level linguistic structures (i.e. phrases and sentences) across the 3 modalities separately. We found that audio-visual integration occurs in all linguistic units, and the brain areas involved in the integration varied across different linguistic levels. In particular, the integration of sentences activated the local left prefrontal area. Therefore, we used continuous theta-burst stimulation to verify that the left prefrontal cortex plays a vital role in the audio-visual integration of sentence information. Our findings suggest the advantage of bimodal language comprehension at hierarchical stages in language-related information processing and provide evidence for the causal role of the left prefrontal regions in processing information of audio-visual sentences.

Complex Mapping between Neural Response Frequency and Linguistic Units in Natural Speech.

When listening to connected speech, the human brain can extract multiple levels of linguistic units, such as syllables, words, and sentences. It has been hypothesized that the time scale of cortical activity encoding each linguistic unit is commensurate with the time scale of that linguistic unit in speech. Evidence for the hypothesis originally comes from studies using the frequency-tagging paradigm that presents each linguistic unit at a constant rate, and more recently extends to studies on natural speech. For natural speech, it is sometimes assumed that neural encoding of different levels of linguistic units is captured by the neural response tracking speech envelope in different frequency bands (e.g., around 1 Hz for phrases, around 2 Hz for words, and around 4 Hz for syllables). Here, we analyze the coherence between speech envelope and idealized responses, each of which tracks a single level of linguistic unit. Four units, that is, phones, syllables, words, and sentences, are separately considered. We show that the idealized phone-, syllable-, and word-tracking responses all correlate with the speech envelope both around 3-6 Hz and below ∼1 Hz. Further analyses reveal that the 1-Hz correlation mainly originates from the pauses in connected speech. The results here suggest that a simple frequency-domain decomposition of envelope-tracking activity cannot separate the neural responses to different linguistic units in natural speech.

Dual interaction between heartbeat-evoked responses and stimuli.

Heartbeat-evoked responses (HERs) can interact with external stimuli and play a crucial role in shaping perception, self-related processes, and emotional processes. On the one hand, the external stimulus could modulate HERs. On the other hand, the HERs could affect cognitive processing of the external stimulus. Whether the same neural mechanism underlies these two processes, however, remains unclear. Here, we investigated this interactive mechanism by measuring HERs using magnetoencephalography (MEG) and two name perception tasks. Specifically, we tested (1) how hearing a subject's own name (SON) modulates HERs and (2) how the judgment of an SON is biased by prestimulus HERs. The results showed a dual interaction between HERs and SON. In particular, SON can modulate HERs for heartbeats occurring from 200 to 1200 ms after SON presentation. In addition, prestimulus HERs can bias the SON judgment when a stimulus is presented. Importantly, MEG activities from these two types of interactions differed in spatial and temporal patterns, suggesting that they may be associated with distinct neural pathways. These findings extend our understanding of brain-heart interactions.

METTL3 promotes proliferation of goat endometrial epithelial cells by regulating CTGF in an m6A-dependent manner†.

N6-methyladenosine (m6A), an epigenetic modification on RNAs, plays an important role in many physiological and pathological processes. However, the involvement of m6A in goat uterus during early pregnancy remains largely unknown. In this study, we found that the total m6A level was increasing in goat uterus as early pregnancy progressed. Methyltransferase-like 3 (METTL3) is a core catalytic subunit of the m6A methyltransferase. We thus determined the expression and regulation of METTL3 in goat uterus. METTL3 was highly expressed in the luminal and glandular epithelia from day 16 (D16) to D25 of pregnancy, and it could be up-regulated by estrogen and progesterone in goat uterus and primary endometrial epithelial cells (EECs). In EECs, knockdown or overexpression of METTL3 resulted in a significant decrease or increase of cell proliferation, respectively. METTL3 knockdown reduced the m6A level of not only total RNA but also connective tissue growth factor (CTGF) mRNA. Luciferase assay suggested that METTL3 might target the potential m6A sites in the 3'untranslated region (3'UTR) of CTGF mRNA. Moreover, METTL3 positively regulated CTGF expression, and CTGF knockdown significantly counteracted the promoting effect of METTL3 overexpression on EEC proliferation. Collectively, METTL3 is dynamically expressed in goat uterus and can affect EEC proliferation by regulating CTGF in an m6A-dependent manner. Our results will lay a foundation for further studying the crucial mechanism of METTL3-mediated m6A modification in goat uterus during early pregnancy.

An IFNT/FOXO1/PTGS2 axis regulates prostaglandin F2α synthesis in goat uterus during early pregnancy.

In ruminants, IFN-tau (IFNT) regulates the production of prostaglandins (PG) in the endometrium, which is crucial for conceptus adhesion. However, the related molecular regulatory mechanisms remain unclear. Forkhead box O1 (FOXO1), a member of the FOXO subfamily of transcription factors, is known to be important for mouse implantation and decidualization. In this study, we determined the spatiotemporal expression profile of FOXO1 in goat endometrium during early pregnancy. FOXO1 was highly expressed in the glandular epithelium since the onset of conceptus adhesion (d 16 of pregnancy). Then, we validated that FOXO1 could bind to the promoter of prostaglandin-endoperoxide synthase 2 (PTGS2) and increase its transcription. And the expression profile of PTGS2 was similar to that of FOXO1 in the peri-implantation uterus. Moreover, IFNT could upregulate the levels of FOXO1 and PTGS2 in goat uterus and primary endometrial epithelium cells (EEC). In EEC, the intracellular content of PGF2α was positively correlated with the levels of IFNT and FOXO1. Altogether, we found an IFNT/FOXO1/PTGS2 axis that controls the synthesis of PGF2α but not prostaglandin E2 in goat uterine glands. These findings contribute to better understanding the function of FOXO1 in the reproductive physiology of goats and provide more insights into the implantation of small ruminants.

Asymmetrical cross-modal influence on neural encoding of auditory and visual features in natural scenes.

Natural scenes contain multi-modal information, which is integrated to form a coherent perception. Previous studies have demonstrated that cross-modal information can modulate neural encoding of low-level sensory features. These studies, however, mostly focus on the processing of single sensory events or rhythmic sensory sequences. Here, we investigate how the neural encoding of basic auditory and visual features is modulated by cross-modal information when the participants watch movie clips primarily composed of non-rhythmic events. We presented audiovisual congruent and audiovisual incongruent movie clips, and since attention can modulate cross-modal interactions, we separately analyzed high- and low-arousal movie clips. We recorded neural responses using electroencephalography (EEG), and employed the temporal response function (TRF) to quantify the neural encoding of auditory and visual features. The neural encoding of sound envelope is enhanced in the audiovisual congruent condition than the incongruent condition, but this effect is only significant for high-arousal movie clips. In contrast, audiovisual congruency does not significantly modulate the neural encoding of visual features, e.g., luminance or visual motion. In summary, our findings demonstrate asymmetrical cross-modal interactions during the processing of natural scenes that lack rhythmicity: Congruent visual information enhances low-level auditory processing, while congruent auditory information does not significantly modulate low-level visual processing.

Delta-band neural activity primarily tracks sentences instead of semantic properties of words.

Human language is generally combinatorial: Words are combined into sentences to flexibly convey meaning. How the brain represents sentences, however, remains debated. Recently, it has been shown that delta-band cortical activity correlates with the sentential structure of speech. It remains debated, however, whether delta-band cortical tracking of sentences truly reflects mental representations of sentences or is caused by neural encoding of semantic properties of individual words. The current study investigates whether delta-band neural tracking of speech can be explained by semantic properties of individual words. Cortical activity is recorded using electroencephalography (EEG) when participants listen to sentences repeating at 1 Hz and word lists. The semantic properties of individual words, simulated using a word2vec model, predict a stronger 1 Hz response to word lists than to sentences. When listeners perform a word-monitoring task that does not require sentential processing, the 1 Hz response to word lists, however, is much weaker than the 1 Hz response to sentences, contradicting the prediction of the lexical semantics model. When listeners are explicitly asked to parse word lists into multi-word chunks, however, cortical activity can reliably track the multi-word chunks. Taken together, these results suggest that delta-band neural responses to speech cannot be fully explained by the semantic properties of single words and are potentially related to the neural representation of multi-word chunks.

Working memory asymmetrically modulates auditory and linguistic processing of speech.

Working memory load can modulate speech perception. However, since speech perception and working memory are both complex functions, it remains elusive how each component of the working memory system interacts with each speech processing stage. To investigate this issue, we concurrently measure how the working memory load modulates neural activity tracking three levels of linguistic units, i.e., syllables, phrases, and sentences, using a multiscale frequency-tagging approach. Participants engage in a sentence comprehension task and the working memory load is manipulated by asking them to memorize either auditory verbal sequences or visual patterns. It is found that verbal and visual working memory load modulate speech processing in similar manners: Higher working memory load attenuates neural activity tracking of phrases and sentences but enhances neural activity tracking of syllables. Since verbal and visual WM load similarly influence the neural responses to speech, such influences may derive from the domain-general component of WM system. More importantly, working memory load asymmetrically modulates lower-level auditory encoding and higher-level linguistic processing of speech, possibly reflecting reallocation of attention induced by mnemonic load.

Evolution of Potato virus X.

Potato virus X (PVX) is the type potexvirus of economic significance. The pathogen is distributed worldwide, threatening solanaceous plants in particular. Based on the coat protein (CP) gene, PVX isolates are classified into two major genotypes (I and II). To gain more insights into the molecular epidemiology and evolution of PVX, recombination analyses were conducted and significant signals were detected. Bayesian coalescent method was then applied to the time-stamped entire CP sequences. According to the estimates, the global subtype I-1 went into expansion in the 20th century and was evolving at a moderate rate. Based on the CP phylogenies, a divergence scenario was proposed for PVX. Surveys of codon usage variation showed that PVX genes had additional bias independent of compositional constraint. In codon preference, PVX was both similar to and different from the three major hosts, potato (Solanum tuberosum), tobacco (Nicotiana tabacum), and tomato (S. lycopersicum). Moreover, the suppression of CpG and UpA dinucleotide frequencies was observed in PVX.

YY1 and RTCB in mouse uterine decidualization and embryo implantation.

As a multifunctional transcription factor, YY1 regulates the expression of many genes essential for early embryonic development. RTCB is an RNA ligase that plays a role in tRNA maturation and Xbp1 mRNA splicing. YY1 can bind in vitro to the response element in the proximal promoter of Rtcb and regulate Rtcb promoter activity. However, the in vivo regulation and whether these two genes are involved in the mother-fetal dialogue during early pregnancy remain unclear. In this study, we validated that YY1 bound in vivo to the proximal promoter of Rtcb in mouse uterus of early pregnancy. Moreover, via building a variety of animal models, our study suggested that both YY1 and RTCB might play a role in mouse uterus decidualization and embryo implantation during early pregnancy.

[Expression and regulation of XBP1 in mouse uterus during early pregnancy].

The transcription factor X-box binding protein-1 (XBP1) plays a key role in unfolded protein reaction. This study was aimed to investigate the expression pattern and regulation of XBP1 in the mouse uterus during early pregnancy. The methods of immunohistochemistry (IHC) and real time quantitative RT-PCR were used to test XBP1 expression in early pregnancy, artificial decidualization, oestrous cycle and hormone-regulated mouse models. The results showed that XBP1 was spatiotemporally expressed in mouse uterus during early pregnancy. The XBP1 protein was mainly detected in the luminal and glandular epithelia on days 1-4 of pregnancy, and was strongly detected in the decidual area on days 5-8 of pregnancy. Similarly, XBP1 expression was also mainly expressed in decidual cells following artificial decidualization. During the oestrous cycle, Xbp1, Xbp1u, and Xbp1s mRNA was predominantly present in proestrus. In the ovariectomized uterus, the expression of XBP1 in luminal and glandular epithelia was up-regulated after estrogen treatment. These results suggest that XBP1 is associated with embryo implantation and decidualization during early pregnancy in mice, and the expression of XBP1 in luminal and glandular epithelia may be regulated by estrogen.

Understanding Requires Tracking: Noise and Knowledge Interact in Bilingual Comprehension.

Understanding speech in noise is a fundamental challenge for speech comprehension. This perceptual demand is amplified in a second language: It is a common experience in bars, train stations, and other noisy environments that degraded signal quality severely compromises second language comprehension. Through a novel design, paired with a carefully selected participant profile, we independently assessed signal-driven and knowledge-driven contributions to the brain bases of first versus second language processing. We were able to dissociate the neural processes driven by the speech signal from the processes that come from speakers' knowledge of their first versus second languages. The neurophysiological data show that, in combination with impaired access to top-down linguistic information in the second language, the locus of bilinguals' difficulty in understanding second language speech in noisy conditions arises from a failure to successfully perform a basic, low-level process: cortical entrainment to speech signals above the syllabic level.

Visual target detection in a distracting background relies on neural encoding of both visual targets and background.

The ability to detect visual targets in complex background varies across individuals and are affected by factors such as stimulus saliency and top-down attention. Here, we investigated how the saliency of visual background (naturalistic cartoon video vs. blank screen) and top-down attention (single vs. dual tasks) separately affect individual ability to detect visual targets. Behaviorally, we found that target detection accuracy decreased and reaction time elongated when the background was salient or during dual tasking. The EEG response to visual background was recorded using a novel stimulus tagging technique. This response was strongest in occipital electrodes and was sensitive to background saliency but not dual tasking. In contrast, the event-related potential (ERP) evoked by the visual target was strongest in central electrodes, and was affected by both background saliency and dual tasking. With a cartoon background, the EEG responses to visual targets, presented in the central visual field, and the EEG responses to peripheral visual background could both predict individual target detection performance. When these two responses were combined, better prediction was achieved. These results suggest that neural processing of visual targets and background jointly contribute to individual visual target detection performance.