Neural Processing Research Articles

Loss of Lkb1 cooperates with BrafV600E and ultraviolet radiation, increasing melanoma multiplicity and neural-like dedifferentiation.

The mechanisms that work alongside BRAFV600E oncogene in melanoma development, in addition to ultraviolet (UV) radiation (UVR), are of great interest. Analysis of human melanoma tumors [data from The Cancer Genome Atlas (TCGA)] revealed that 50% or more of the samples expressed no or low amounts of serine/threonine protein kinase STK11 (also known as LKB1) protein. Here, we report that, in a mouse model, concomitant neonatal BrafV600E activation and Lkb1 tumor suppressor ablation in melanocytes led to full melanoma development. A single postnatal dose of UVB radiation had no effect on melanoma onset in Lkb1-depleted mice compared with BrafV600E-irradiated mice, but increased tumor multiplicity. In concordance with these findings and previous reports, Lkb1-null irradiated mice exhibited deficient DNA damage repair (DDR). Histologically, tumors lacking Lkb1 were enriched in neural-like tumor morphology. Genetic profiling and gene set enrichment analyses of tumor sample mutated genes indicated that loss of Lkb1 promoted the selection of altered genes associated with neural differentiation processes. Thus, these results suggest that the loss of Lkb1 cooperates with BrafV600E and UVR, impairing the DDR and increasing melanoma multiplicity and neural-like dedifferentiation.

Benefit of Modulated Masking in hearing according to age

ObjectiveTo analyze the Benefit of Modulated Masking (BMM) on hearing in young, adult and elderly normal-hearing individuals. MethodsThe sample included 60 normal-hearing individuals aged 18–75 years who underwent behavioral assessment (sentence recognition test in the presence of steady and modulated noise) and electrophysiological assessment (cortical Auditory Evoked Potential) to investigate BMM. The results were analyzed comparatively using the paired t-test and ANOVA for repeated measures, followed by the Bonferroni post-hoc test (p-value < 0.05). ResultsA decrease in latencies and an increase in amplitudes of cortical components (P1-N1-P2) was observed due to noise modulation in all age groups. Modulated noise generated better auditory threshold responses (electrophysiological and behavioral), compared to steady noise. The elderly presented a higher threshold in both hearing domains, compared to the other participants, as well as a lower BMM magnitude. ConclusionIt was possible to conclude that the modulated noise generated less interference in the magnitude of the neural response (smaller latencies) and in the neural processing time (larger amplitudes) for the speech stimulus in all participants. The higher auditory thresholds (electrophysiological and behavioral) and the lower BMM magnitude observed in the elderly group, even in the face of noise modulation, suggest a lower temporal auditory performance in this population, and may indicate a deficit in the temporal resolution capacity, associated with the process of aging. Level of evidence3.

Presentation of multiple task instructional sets impacts auditory Stroop performance during dual task locomotion.

The auditory Stroop is a modification of the classic Stroop paradigm commonly used in dual-task research when the motor task requires the visual system. Despite its use, there are gaps in our understanding of this tool. For example, in visual/auditory Stroop paradigms, neutral cues irrelevant to the required response, which theoretically cause less interference/facilitation, are used to elucidate effects of visual/auditory demands on neural processes. Specifically, in auditory Stroop paradigms the use and choice of neutral cue words is inconsistent. To address these gaps, we instrumented participants with kinematic markers and a digital microphone and asked them to respond to auditory Stroop cues and neutral cue words consisting of either one or two syllables, while simultaneously performing an unobstructed locomotor task. Two blocks of trials were collected. In one block, participants had prior knowledge that either an auditory Stroop or a neutral word stimulus would be presented (Known); a second block presented both types of cognitive cues in a random order to participants (Mixed). We observed main effects of cognitive task (neutral, incongruent, congruent) and instructional set (Known, Mixed) on response times, but not on center of mass velocity. Also, more time was required to verbally respond to an incongruent compared to congruent or neutral task across all conditions, and neutral task words with one syllable resulted in longer response times compared to two syllable neutral words. We recommend that researchers include neutral cues when using the auditory Stroop test and to carefully consider their neutral word choice.

Neural Processing of Taste-Related Signals in the Mediodorsal Thalamus of Mice.

Our consummatory decisions depend on the taste of food and the reward experienced while eating, which are processed through neural computations in interconnected brain areas. Although many gustatory regions of rodents have been explored, the mediodorsal nucleus of the thalamus (MD) remains understudied. The MD, a multimodal brain area connected with gustatory centers, is often studied for its role in processing associative and cognitive information and has been shown to represent intraorally-delivered chemosensory stimuli after strong retronasal odor-taste associations. Key questions remain about whether MD neurons can process taste quality independently of odor-taste associations and how they represent extraoral signals predicting rewarding and aversive gustatory outcomes. Here, we present electrophysiological evidence demonstrating how mouse MD neurons represent and encode 1) the identity and concentrations of basic taste qualities during active licking, and 2) auditory signals anticipating rewarding and aversive taste outcomes. Our data reveal that MD neurons can reliably and dynamically encode taste identity in a broadly tuned manner and taste concentrations with spiking activity positively and negatively correlated with stimulus intensity. Our data also show that MD can represent information related to predictive cues and their associated outcomes, regardless of whether the cue predicts a rewarding or aversive outcome. In summary, our findings suggest that the mediodorsal thalamus is integral to the taste pathway, as it can encode sensory-discriminative dimensions of tastants and participate in processing associative information essential for ingestive behaviors.

Lateralization of acquisition and consolidation in direction but not amplitude of a motor skill task.

Previous research suggests that the neural processes underlying specification of movement direction and amplitude are independently represented in the nervous system. However, our understanding of acquisition and consolidation processes in the direction and distance learning remains limited. We designed a virtual air hockey task, in which the puck direction is determined by the hand direction at impact, while the puck distance is determined by the amplitude of the velocity. In two versions of this task, participants were required to either specify the direction or the distance of the puck, while the alternate variable did not contribute to task success. Separate groups of right-handed participants were recruited for each task. Each participant was randomly assigned to one of two groups with a counter-balanced arm practice sequence (right to left, or left to right). We examined acquisition and, after 24h, we examined two aspects of consolidation: 1) same hand performance to test the durability and 2)the opposite hand to test the effector-independent consolidation (interlimb transfer) of learning. The distance task showed symmetry between hands in the extent of acquisition as well as in both aspects of consolidation. In contrast, the direction task showed asymmetry in both acquisition and consolidation: the dominant right arm showed faster and greater acquisition and greater transfer from the opposite arm training. The asymmetric acquisition and consolidation processes shown in the direction task might be explained by lateralized control and mapping of direction, an interpretation consistent with previous findings on motor adaptation paradigms.

The characteristics and reproducibility of motor speech functional neuroimaging in healthy controls.

Functional magnetic resonance imaging (fMRI) can improve our understanding of neural processes subserving motor speech function. Yet its reproducibility remains unclear. This study aimed to evaluate the reproducibility of fMRI using a word repetition task across two time points. Imaging data from 14 healthy controls were analysed using a multi-level general linear model. Significant activation was observed during the task in the right hemispheric cerebellar lobules IV-V, right putamen, and bilateral sensorimotor cortices. Activation between timepoints was found to be moderately reproducible across time in the cerebellum but not in other brain regions. Preliminary findings highlight the involvement of the cerebellum and connected cerebral regions during a motor speech task. More work is needed to determine the degree of reproducibility of speech fMRI before this could be used as a reliable marker of changes in brain activity.

Computational model for synthesizing auditory brainstem responses to assess neuronal alterations in aging and autistic animal models.

This study presents a novel computational model of the auditory brainstem, capable of synthesizing auditory brainstem response (ABR) traces by simulating large-scale neuronal activities. Addressing limitations of traditional ABR measurements, the model links ABR waveform features to underlying neuronal properties. Validated using empirical ABRs from animal models of autism and aging, the model accurately reproduced observed ABR alterations, revealing influences of myelin deficits and hyperexcitability in Fragile X syndrome, and degraded inhibitory activity in aging. These findings, supported by experimental data, demonstrate the model's potential for predicting changes in auditory brainstem physiology and guiding further physiological investigations, thus advancing our understanding of auditory neural processes.

Conflict Detection in Language Processing: Using Affect Control Theory to Predict Neural Correlates of Affective Incongruency in Social Interactions

Affect control theory (ACT) is a sociological theory of meaning processing in social interactions. Meaning, according to ACT, derives from cultural institutions and situational affordances, having denotative (declarative) as well as connotative (affective) properties. Mathematical formalizations of ACT allow predictions of affective incongruency (in the terminology of ACT, deflection), which arises from conflicting institutional and situational meanings in a given interaction context. Although ACT is theoretically consistent, its propositions regarding cognitive and affective processing have rarely been tested. The present study fills this gap by investigating the neural processing of affective incongruency in linguistic descriptions of social interactions. Following a neurosociological paradigm, the study draws on neurocognitive evidence on the effects of words’ affective content on word processing as well as on a previous electroencephalography study that investigated processing of affective incongruency using event-related brain potentials. We hypothesized that affective incongruency is associated with activation in the anterior cingulate cortex (ACC), a brain area known for conflict processing. To test this hypothesis, we replicated the electroencephalography study using functional magnetic resonance imaging: We visually presented sentences describing social interactions to 23 participants in a silent reading task while measuring differences in the hemodynamic response in two conditions of affective congruency. Results show expected increases in neural activity for affectively incongruent sentences in the left ACC, supporting the assumption that affective language content influences meaning-making at very early semantic processing stages. The results also add to the emerging neuroscientific evidence for ACT’s mathematical model of impression formation.

Neural evidence of core foundations and conceptual change in preschool numeracy.

Symbolic numeracy first emerges as children learn the meanings of number words and how to use them to precisely count sets of objects. This development starts before children enter school and forms a foundation for lifelong mathematics achievement. Despite its importance, exactly how children acquire this basic knowledge is unclear. Here we test competing theories of early number learning by measuring event-related brain potentials during a novel number word-quantity comparison task in 3-4-year-old preschool children (N=128). We find several qualitative differences in neural processing of number by conceptual stage of development. Specifically, we find differences in early attention-related parietal electrophysiology (N1), suggesting that less conceptually advanced children process arrays as individual objects and more advanced children distribute attention over the entire set. Subsequently, we find that only more conceptually advanced children show later-going frontal (N2) sensitivity to the numerical-distance relationship between the number word and visual quantity. The nature of this response suggested thatexact rather than approximate numerical meanings were being associated with number words over frontal sites. No evidence of numerical distance effects was observed over posterior scalp sites. Together these results suggest that children may engage parallel individuation of objects to learn the meanings of the first few number words, but, ultimately, create new exact cardinal value representations for number words that cannot be defined in terms of core, nonverbal number systems. More broadly, these results document an interaction between attentional and general cognitive mechanisms in cognitive development. RESEARCH HIGHLIGHTS: Conceptual development in numeracy is associated with a shift in attention from objects to sets. Children acquire meanings of the first few number words through associations with parallel attentional individuation of objects. Understanding of cardinality is associated with attentional processing of sets rather than individuals. Brain signatures suggest children attribute exact rather than approximate numerical meanings to the first few number words. Number-quantity relationship processing for the first few number words is evident in frontal but not parietal scalp electrophysiology of young children.

A single-nucleus transcriptomic atlas of medium spiny neurons in the rat nucleus accumbens

Neural processing of rewarding stimuli involves several distinct regions, including the nucleus accumbens (NAc). The majority of NAc neurons are GABAergic projection neurons known as medium spiny neurons (MSNs). MSNs are broadly defined by dopamine receptor expression, but evidence suggests that a wider array of subtypes exist. To study MSN heterogeneity, we analyzed single-nucleus RNA sequencing data from the largest available rat NAc dataset. Analysis of 48,040 NAc MSN nuclei identified major populations belonging to the striosome and matrix compartments. Integration with mouse and human data indicated consistency across species and disease-relevance scoring using genome-wide association study results revealed potentially differential roles for MSN populations in substance use disorders. Additional high-resolution clustering identified 34 transcriptomically distinct subtypes of MSNs definable by a limited number of marker genes. Together, these data demonstrate the diversity of MSNs in the NAc and provide a basis for more targeted genetic manipulation of specific populations.

Generic masculine role nouns interfere with the neural processing of female referents: evidence from the P600

ABSTRACT The masculine form in German is used to refer to male people specifically and to people of any gender generically. While behavioural research has demonstrated that this dual function leads to male-biased responses, the neural underpinnings of this bias are still underexplored. In the present EEG study, we investigated how the presentation of generically intended masculine role nouns (vs. role nouns in the feminine–masculine and masculine–feminine pair form) affected the neural processing of references to men and women. Referring to women after generic masculine role nouns induced difficulties during perceptual processing in the P200 range and, crucially, also during high-level reference resolution, as indicated by an enhanced P600 amplitude over posterior sites. In contrast, no significant processing conflicts were observed after the pair form. These findings illuminate the neural consequences of grammatical gender and support the notion that the generic masculine does not represent different genders equally well.

2D Super-Resolution Metrology Based on Superoscillatory Light.

Progress in the semiconductor industry relies on the development of increasingly compact devices consisting of complex geometries made from diverse materials. Precise, label-free, and real-time metrology is needed for the characterization and quality control of such structures in both scientific research and industry. However, optical metrology of 2D sub-wavelength structures with nanometer resolution remains a major challenge. Here, a single-shot and label-free optical metrology approach that determines 2D features of nanostructures, is introduced. Accurate experimental measurements with a random statistical error of 18nm (λ/27) are demonstrated, while simulations suggest that 6nm (λ/81) may be possible. This is far beyond the diffraction limit that affects conventional metrology. This metrology employs neural network processing of images of the 2D nano-objects interacting with a phase singularity of the incident topologically structured superoscillatory light. A comparison between conventional and topologically structured illuminations shows that the presence of a singularity with a giant phase gradient substantially improves the retrieval of object information in such an optical metrology. This non-invasive nano-metrology opens a range of application opportunities for smart manufacturing processes, quality control, and advanced materials characterization.

Distinct Neural Plasticity Enhancing Visual Perception.

The developed human brain shows remarkable plasticity following perceptual learning, resulting in improved visual sensitivity. However, such improvements commonly require extensive stimuli exposure. Here we show that efficiently enhancing visual perception with minimal stimuli exposure recruits distinct neural mechanisms relative to standard repetition-based learning. Participants (n = 20, 12 women, 8 men) encoded a visual discrimination task, followed by brief memory reactivations of only five trials each performed on separate days, demonstrating improvements comparable with standard repetition-based learning (n = 20, 12 women, 8 men). Reactivation-induced learning engaged increased bilateral intraparietal sulcus (IPS) activity relative to repetition-based learning. Complementary evidence for differential learning processes was further provided by temporal-parietal resting functional connectivity changes, which correlated with behavioral improvements. The results suggest that efficiently enhancing visual perception with minimal stimuli exposure recruits distinct neural processes, engaging higher-order control and attentional resources while leading to similar perceptual gains. These unique brain mechanisms underlying improved perceptual learning efficiency may have important implications for daily life and in clinical conditions requiring relearning following brain damage.

Natural generative noise diffusion model imputation

Imputation is a critical method for enhancing dataset quality, essential for ensuring accurate analysis and insights. This research proposes an advanced imputation algorithm utilizing a Diffusion Model enhanced with Perlin noise generation. We introduce Perlin noise at each step of the diffusion process and incorporate a cosine scheduler to optimize performance. Our approach demonstrates improvements in imputing non-normal data, validated through tests on ten real datasets. Due to the substantial slope of distribution properties produced by perlin noise, noisy data gradually contaminates nonnormally distributed data, making it more like to a Gaussian distribution. The Perlin noise distribution increases the normality of the noisy data provided noise when it enters the deep neural process of diffusion imputation. We assess our proposed approach by simulating the missing data rate using three scenarios: Missing Completely at Random (MCAR), Missing Not At Random (MNAR), and Missing at Random (MAR). Every case is handled similarly, with 20 % to 80 % missing data. Compared to other deep learning imputation methods, our proposed methods and improvements contribute to lowering the RMSE value up to 10 % on non-normal distributed data imputation.

Aberrance in default mode and executive network activity underlie working memory deficits in addictive disorders: A preliminary, exploratory case-control study

BackgroundAddiction can alter neural processes during rest and cognitive performance. Subjects with addictive disorders exhibit preoccupation and anticipation for the psychoactive substance when idle and cognitive deficits, during tasks. Methods128 channel EEG was recorded in sixty subjects (30, with alcohol, opioid and internet addiction; 30 controls) during rest and while performing working memory task to ascertain underlying differences in cortical activity between the groups while at rest and during performance of the task. Artifactually clean data was then subjected to source analysis using sLORETA software in both the groups. ResultsEEG cortical source analysis in subjects with addictive disorders showed significant activation of areas of Default Mode Network (DMN) and reduced activation in dorsolateral prefrontal cortices (DLPFC), an area known to be involved in executive function, during performance of task. However, control subjects demonstrated significantly reduced activation in areas of DMN; and increased activation of DLPFC during task performance. ConclusionInability to suppress DMN inhibits reallocation of neural resources to areas of executive functioning leading to working memory deficits in subjects with addictive disorder.

Optogenetic Stimulation of Nociceptive Escape Behaviors in Drosophila Larvae.

In animals, noxious stimuli activate a neural process called nociception. Drosophila larvae perform a rolling escape locomotion behavior in response to nociceptive sensory stimuli. Noxious mechanical, thermal, and chemical stimuli each trigger this same escape response in larvae. The polymodal sensory neurons that initiate the rolling response have been identified based on the expression patterns of genes that are known to be required for nociception responses. The synaptic output of these neurons, known as class IV multidendritic sensory neurons, is required for behavioral responses to thermal, mechanical, and chemical triggers of the rolling escape locomotion. Importantly, optogenetic stimulation of the class IV multidendritic neurons has also shown that the activation of those cells is sufficient to trigger nociceptive rolling. Optogenetics uses light-activated ion channels expressed in neurons of interest to bypass the normal physiological transduction machinery so that the cell may be activated in response to light that is applied by the investigator. This protocol describes an optogenetic technique that uses channelrhodopsin-2 (ChR2) to activate larval nociceptors and trigger nociceptive rolling. First, we explain how to set up the necessary genetic crosses and culture the larval progeny. Next, we describe how to perform the optogenetic nociception assay on third-instar larvae.

Neural tracking of speech acoustics in noise is coupled with lexical predictability as estimated by large language models.

Adults heard recordings of two spatially separated speakers reading newspaper and magazine articles. They were asked to listen to one of them and ignore the other, and EEG was recorded to assess their neural processing. Machine learning extracted neural sources that tracked the target and distractor speakers at three levels: the acoustic envelope of speech (delta- and theta-band modulations), lexical frequency for individual words, and the contextual predictability of individual words estimated by GPT-4 and earlier lexical models. To provide a broader view of speech perception, half of the subjects completed a simultaneous visual task, and the listeners included both native and non-native English speakers. Distinct neural components were extracted for these levels of auditory and lexical processing, demonstrating that native English speakers had greater target-distractor separation compared to non-native English speakers on most measures, and that lexical processing was reduced by the visual task. Moreover, there was a novel interaction of lexical predictability and frequency with auditory processing; acoustic tracking was stronger for lexically harder words, suggesting that people listened harder to the acoustics when needed for lexical selection. This demonstrates that speech perception is not simply a feedforward process from acoustic processing to the lexicon. Rather, the adaptable context-sensitive processing long known to occur at a lexical level has broader consequences for perception, coupling with the acoustic tracking of individual speakers in noise.Significance Statement In challenging listening conditions, people use focused attention to help understand individual talkers and ignore others, which changes their neural processing for speech at auditory through lexical levels. However, lexical processing for natural materials (e.g., conversations, audiobooks) has been difficult to measure, because of limitations of tools to estimate the predictability of individual words in longer discourses. The present investigation uses a contemporary large language model, GPT-4, to estimate word predictability, and demonstrates that listeners make online adaptations to their auditory neural processing in accord with these predictions; neural activity more closely tracks the acoustics of the target talker when words are less predictable from the context.

Brain and grammar: revealing electrophysiological basic structures with competing statistical models.

Acoustic, lexical, and syntactic information are simultaneously processed in the brain requiring complex strategies to distinguish their electrophysiological activity. Capitalizing on previous works that factor out acoustic information, we could concentrate on the lexical and syntactic contribution to language processing by testing competing statistical models. We exploited electroencephalographic recordings and compared different surprisal models selectively involving lexical information, part of speech, or syntactic structures in various combinations. Electroencephalographic responses were recorded in 32 participants during listening to affirmative active declarative sentences. We compared the activation corresponding to basic syntactic structures, such as noun phrases vs. verb phrases. Lexical and syntactic processing activates different frequency bands, partially different time windows, and different networks. Moreover, surprisal models based on part of speech inventory only do not explain well the electrophysiological data, while those including syntactic information do. By disentangling acoustic, lexical, and syntactic information, we demonstrated differential brain sensitivity to syntactic information. These results confirm and extend previous measures obtained with intracranial recordings, supporting our hypothesis that syntactic structures are crucial in neural language processing. This study provides a detailed understanding of how the brain processes syntactic information, highlighting the importance of syntactic surprisal in shaping neural responses during language comprehension.

KineWheel-DeepLabCut Automated Paw Annotation Using Alternating Stroboscopic UV and White Light Illumination.

Uncovering the relationships between neural circuits, behavior, and neural dysfunction may require rodent pose tracking. While open-source toolkits such as DeepLabCut have revolutionized markerless pose estimation using deep neural networks, the training process still requires human intervention for annotating key points of interest in video data. To further reduce human labor for neural network training, we developed a method that automatically generates annotated image datasets of rodent paw placement in a laboratory setting. It uses invisible but fluorescent markers that become temporarily visible under UV light. Through stroboscopic alternating illumination, adjacent video frames taken at 720 Hz are either UV or white light illuminated. After color filtering the UV-exposed video frames, the UV markings are identified and the paw locations are deterministically mapped. This paw information is then transferred to automatically annotate paw positions in the next white light-exposed frame that is later used for training the neural network. We demonstrate the effectiveness of our method using a KineWheel-DeepLabCut setup for the markerless tracking of the four paws of a harness-fixed mouse running on top of the transparent wheel with mirror. Our automated approach, made available open-source, achieves high-quality position annotations and significantly reduces the need for human involvement in the neural network training process, paving the way for more efficient and streamlined rodent pose tracking in neuroscience research.

Multi-timescale neural dynamics for multisensory integration.

Carrying out any everyday task, be it driving in traffic, conversing with friends or playing basketball, requires rapid selection, integration and segregation of stimuli from different sensory modalities. At present, even the most advanced artificial intelligence-based systems are unable to replicate the multisensory processes that the human brain routinely performs, but how neural circuits in the brain carry out these processes is still not well understood. In this Perspective, we discuss recent findings that shed fresh light on the oscillatory neural mechanisms thatmediate multisensory integration (MI), including power modulations, phase resetting, phase-amplitude coupling and dynamic functional connectivity. We then consider studies that also suggest multi-timescale dynamics in intrinsic ongoing neural activity and during stimulus-driven bottom-up and cognitive top-down neural network processing in the context of MI. We propose a new concept of MI that emphasizes the critical role of neural dynamics at multiple timescales within and across brain networks, enabling the simultaneous integration, segregation, hierarchical structuring and selection of information in different time windows. To highlight predictions from our multi-timescale concept of MI, real-world scenarios in which multi-timescale processes may coordinate MI in a flexible and adaptive manner are considered.