Information Processing In Brain Research Articles

Enigma of Pyramidal Neurons: Chirality-Centric View on Biological Evolution. Congruence to Molecular, Cellular, Physiological, Cognitive, and Psychological Functions

The mechanism of brain information processing unfolds within spatial and temporal domains inherently linked to the concept of space–time symmetry. Biological evolution, beginning with the prevalent molecular chirality, results in the handedness of human cognitive and psychological functions (the phenomena known as biochirality). The key element in the chain of chirality transfer from the downstream to upstream processes is the pyramidal neuron (PyrN) morphology–function paradigm (archetype). The most apparent landmark of PyrNs is the geometry of the cell soma. However, “why/how PyrN’s soma gains the shape of quasi-tetrahedral symmetry” has never been explicitly articulated. Resolving the above inquiry is only possible based on the broad-view assumption that encoding 3D space requires specific 3D geometry of the neuronal detector and corresponding network. Accordingly, our hypothesis states that if the primary function of PyrNs, at the organism level, is sensory space symmetry perception, then the pyramidal shape of soma is the best evolutionary-selected geometry to support sensory-motor coupling. The biological system’s non-equilibrium (NE) state is fundamentally linked to an asymmetric, non-racemic, steady state of molecular constituents. The chiral theory of pyramidal soma shape conceptually agrees that living systems have evolved as non-equilibrium systems that exchange energy with the environment. The molecular mechanism involved in developing PyrN’s soma is studied in detail. However, the crucial missing element—the reference to the fundamental link between molecular chirality and the function of spatial navigation—is the main obstacle to resolving the question in demand: why did PyrNs’ soma gain the shape of quasi-tetrahedral symmetry?

Cross-frequency coupling in cortico-hippocampal networks supports the maintenance of sequential auditory information in short-term memory.

It has been suggested that cross-frequency coupling in cortico-hippocampal networks enables the maintenance of multiple visuo-spatial items in working memory. However, whether this mechanism acts as a global neural code for memory retention across sensory modalities remains to be demonstrated. Intracranial EEG data were recorded while drug-resistant patients with epilepsy performed a delayed matched-to-sample task with tone sequences. We manipulated task difficulty by varying the memory load and the duration of the silent retention period between the to-be-compared sequences. We show that the strength of theta-gamma phase amplitude coupling in the superior temporal sulcus, the inferior frontal gyrus, the inferior temporal gyrus, and the hippocampus (i) supports the short-term retention of auditory sequences; (ii) decodes correct and incorrect memory trials as revealed by machine learning analysis; and (iii) is positively correlated with individual short-term memory performance. Specifically, we show that successful task performance is associated with consistent phase coupling in these regions across participants, with gamma bursts restricted to specific theta phase ranges corresponding to higher levels of neural excitability. These findings highlight the role of cortico-hippocampal activity in auditory short-term memory and expand our knowledge about the role of cross-frequency coupling as a global biological mechanism for information processing, integration, and memory in the human brain.

A Whole-Brain Topographic Ontology.

It is a common view that the intricate array of specialized domains in the ventral visual pathway is innately prespecified. What this review postulates is that it is not. We explore the origins of domain specificity, hypothesizing that the adult brain emerges from an interplay between a domain-general map-based architecture, shaped by intrinsic mechanisms, and experience. We argue that the most fundamental innate organization of cortex in general, and not just the visual pathway, is a map-based topography that governs how the environment maps onto the brain, how brain areas interconnect, and ultimately, how the brain processes information.

A role of frontal association cortex in long-term object recognition memory of objects with complex features in rats.

Perirhinal cortex is a brain area that has been considered crucial for the object recognition memory (ORM). However, with the use of an ORM enhancer named RGS14414 as gain-in-function tool, we show here that frontal association cortex and not the Perirhinal cortex is essential for the ORM of objects with complex features that consisted of detailed drawing on the object surface (complex ORM). An expression of RGS14414, in rat brain frontal association cortex, induced the formation of long-term complex ORM, whereas the expression of the same memory enhancer in Perirhinal cortex failed to produce this effect. Instead, RGS14414 expression in Perirhinal cortex caused the formation of ORM of objects with simple features that consisted of the shape of object (simple ORM). Further, a selective elimination of frontal association cortex neurons by treatment with an immunotoxin Ox7-SAP completely abrogated the formation of complex ORM. Thus, our results suggest that frontal association cortex plays a key role in processing of a high-order recognition memory information in brain.

Neuroscience In Islamic Religious Education Learning

In the world of education, many discoveries state that humans have not maximized in using the potential of their brains, such as creating new ideas or solving problems. So, this study aims to describe and analyse the relevance of neuroscience in PAI learning and what role neuroscience plays in PAI learning. The methodology applied to this research is a descriptive qualitative method approach, and this research is a type of library research, which is a research based on the source of books, papers, articles, journals and other scientific works that support this research. The results of this study show that neuroscience has a close relationship with PAI learning, where in the implementation of learning neuroscience is needed so that learning can run smoothly and effectively, where neuroscience can help PAI teachers understand better how students’ brains process information and learning materials so that teachers can develop varied teaching strategies and come up with the latest innovations in learning. Neuroscience plays an active role in PAI learning to improve students’ cognitive development.

An evaluation of recent advancements in biological sensory organ-inspired neuromorphically tuned biomimetic devices.

In the field of neuroscience, significant progress has been made regarding how the brain processes information. Unlike computer processors, the brain comprises neurons and synapses instead of memory blocks and transistors. Despite advancements in artificial neural networks, a complete understanding concerning brain functions remains elusive. For example, to achieve more accurate neuron replication, we must better understand signal transmission during synaptic processes, neural network tunability, and the creation of nanodevices featuring neurons and synapses. This study discusses the latest algorithms utilized in neuromorphic systems, the production of synaptic devices, differences between single and multisensory gadgets, recent advances in multisensory devices, and the promising research opportunities available in this field. We also explored the ability of an artificial synaptic device to mimic biological neural systems across diverse applications. Despite existing challenges, neuroscience-based computing technology holds promise for attracting scientists seeking to enhance solutions and augment the capabilities of neuromorphic devices, thereby fostering future breakthroughs in algorithms and the widespread application of cutting-edge technologies.

A STUDY TO ASSESS THE EFFECTIVENESS OF STROOP TASK PERFORMANCE TO IMPROVE VISUAL PERCEPTUAL DISCRIMINATION AMONG VARIOUS CHILDHOOD DISORDERS AT SELECTED HOME, PUDUCHERRY

Background: The Stroop effect is a simple phenomenon that reveals a lot about the brain processes information. The Stroop effect is our tendency to experience difficulty naming a physical color when it is used to spell the name of a different color. It is a neuropsychological test extensively used to assess the ability to inhibit cognitive interference that occurs when the processing of a specific stimulus feature impedes the simultaneous processing of a second stimulus attribute, well-known as the Stroop Effect. The childhood disorder is an any illness, impairment, or abnormal condition that affects primarily infants and children. Some of the childhood disorders like Mild Mental Retardation, Learning Disorders, Motor Skills Disorders, Pervasive Developmental Disorders, Attention Deficit Hyperactive Disorders, Eating disorders of infancy or early childhood, Tic disorders. Visual perceptual discrimination is the brain’s ability to accurately perceive information in a complex, fluid and confusing situation and, even more importantly, to accurately differentiate amongst confusable types of information and ability to identify detail seeing Items like differences in shape, color and orientation. Objectives: The main purpose of this study is to assess the level of visual perceptual discrimination among various childhood disorders. To evaluate the level of visual perceptual discrimination before and after administration of Stroop task performance among various childhood disorders. To associate the level of visual perceptual discrimination among various childhood disorders with their selected demographic variables. Materials and Methods: The research approach used in the study was Quantitative in nature. Pre –Experimental One group Pre- test Post test design was used. Purposive Sampling technique was used to select the samples. A total of 30 Children’s with various childhood disorders were selected for this study. Visual Perceptual Discrimination checklist was used to assess the Visual Perceptual Discrimination Problems among children with childhood disorder and administering stroop task performance using Flashcard was used for intervention and Post test was conducted by using same tool in same manner. Results and Conclusion: The result showed that majority of the childhood disorders at selected home 26(86.7%) had low and 4(13.3%) had moderate level of visual perceptual discrimination during Pre test. The Calculated paired‘t’ value was t= -8.55 and was found to be statistically significant at -P=<0.001 level. After Intervention majority of childhood disorders at selected home 16(53.3%) had low and 14(46.7%) had moderate level of visual perceptual discrimination. There was area of residence and type of childhood disorders had shown statistically significant association between post testlevel of visual perceptual discrimination among various childhood disorders with their selected demographic variables. The other demographic variable had not shown statistically significant association between the post-test level of visual Perceptual discrimination among various childhood disorders with their selected demographic variables .The researcher concluded that by administering Stroop task performance shows that the intervention helps in improving the level of visual perceptual discrimination in good range and found to be one of the helpful interventions in improving the level of visual perceptual discrimination among children with various childhood disorders. The study had proved that Effectiveness and excellent changes in improvement of visual perceptual discrimination among Children\s with various childhood disorders.

Enhancing Computer Digital Signal Processing through the Utilization of RNN Sequence Algorithms

With the increase in computing power and the availability of large amounts of data, deep learning techniques, especially convolutional neural networks (CNNS) and recurrent neural networks (RNNS), have become important tools for processing complex signals. These methods show excellent performance in speech recognition, image processing, natural language processing and so on. In this paper, we explore the application of recurrent neural network (RNN) sequence algorithms in the field of computer digital signal processing, highlighting current artificial intelligence techniques and their capabilities in solving complex signal processing problems. First, the paper reviews the basic principles and development of deep learning and RNN sequence algorithms, highlighting the advances these advanced technologies have made in simulating the way the human brain processes information. The practical application and effect of RNN sequence algorithm in computer digital signal processing are demonstrated through experimental data. By comparing with traditional algorithms, we demonstrate the efficiency and accuracy of RNN in processing complex signals, such as speech recognition in noisy environments and real-time video data processing. The experimental data not only demonstrate the effectiveness of RNNS in this field, but also highlight the unique advantages of deep learning methods when dealing with large and high-dimensional data. Through these empirical studies, this paper aims to provide researchers and engineers with an in-depth understanding of the potential of RNNS in digital signal processing applications, and looks forward to the future development direction of artificial intelligence technology in this field.

Schizophrenia: from neurochemistry to circuits, symptoms and treatments.

Schizophrenia is a leading cause of global disability. Current pharmacotherapy for the diseasepredominantly uses one mechanism - dopamine D2 receptor blockade - but often shows limited efficacy and poor tolerability. These limitations highlight the need to better understand the aetiology of the disease to aid the development of alternative therapeutic approaches. Here, we review the latest meta-analyses and other findings on the neurobiology of prodromal, first-episode and chronic schizophrenia, and the link to psychotic symptoms, focusing on imaging evidence from people with the disorder. This evidence demonstrates regionally specific neurotransmitter alterations, including higher glutamate and dopamine measures in the basal ganglia, and lower glutamate, dopamine and γ-aminobutyric acid (GABA) levels in cortical regions, particularly the frontal cortex, relative to healthy individuals. We consider how dysfunction in cortico-thalamo-striatal-midbrain circuits might alter brain information processing to underlie psychotic symptoms. Finally, we discuss the implications of these findings for developing new, mechanistically based treatments and precision medicine for psychotic symptoms, as well as negative and cognitive symptoms.

Performance Evaluation of Matrix Factorization for fMRI Data.

A hypothesis in the study of the brain is that sparse coding is realized in information representation of external stimuli, which has been experimentally confirmed for visual stimulus recently. However, unlike the specific functional region in the brain, sparse coding in information processing in the whole brain has not been clarified sufficiently. In this study, we investigate the validity of sparse coding in the whole human brain by applying various matrix factorization methods to functional magnetic resonance imaging data of neural activities in the brain. The result suggests the sparse coding hypothesis in information representation in the whole human brain, because extracted features from the sparse matrix factorization (MF) method, sparse principal component analysis (SparsePCA), or method of optimal directions (MOD) under a high sparsity setting or an approximate sparse MF method, fast independent component analysis (FastICA), can classify external visual stimuli more accurately than the nonsparse MF method or sparse MF method under a low sparsity setting.

The dynamic causality brain network reflects whether the working memory is solidified.

Working memory, which is foundational to higher cognitive function, is the "sketchpad of volitional control." Successful working memory is the inevitable outcome of the individual's active control and manipulation of thoughts and turning them into internal goals during which the causal brain processes information in real time. However, little is known about the dynamic causality among distributed brain regions behind thought control that underpins successful working memory. In our present study, given that correct responses and incorrect ones did not differ in either contralateral delay activity or alpha suppression, further rooting on the high-temporal-resolution EEG time-varying directed network analysis, we revealed that successful working memory depended on both much stronger top-down connections from the frontal to the temporal lobe and bottom-up linkages from the occipital to the temporal lobe, during the early maintenance period, as well as top-down flows from the frontal lobe to the central areas as the delay behavior approached. Additionally, the correlation between behavioral performance and casual interactions increased over time, especially as memory-guided delayed behavior approached. Notably, when using the network metrics as features, time-resolved multiple linear regression of overall behavioral accuracy was exactly achieved as delayed behavior approached. These results indicate that accurate memory depends on dynamic switching of causal network connections and shifting to more task-related patterns during which the appropriate intervention may help enhance memory.

Integration of Ibn Sina’s Universal Language Theory and Neuroscience in the Development of Learning Media

The current research attempted to integrate Ibn Sina's universal language theory and neuroscience in the development of learning media. It adopted a qualitative library method, with data collected from literature related to universal language theory, neuroscience, and the development of learning materials of Ibn Sina through manual and digital searches for relevant references. The data collected was analyzed by using content analysis which encompassed the data reduction, presentation, and the synthesis of new and comprehensive conceptual frameworks. The results showed that Ibn Sina’s universal language theory offered valuable insights into the significance of language in communication and cognition. Neuroscience provided an understanding of how the human brain processes information and learns. The concepts associated with Ibn Sina's universal language theory and neuroscience, including elements, such as signs, meaning, and relationship between language and reality, were explored to examine their influence on learning media development. The understanding of the principles of human brain-based learning, based on the results of neuroscience, served as a foundation for effective learning media development. By integrating these attributes, the development of learning materials incorporated the conveyance of information in harmony with universal language comprehension and brain-based learning principles. Therefore, learning material developers and teachers should create instructional methods in accordance with advancements in science and technology.

Sparsity in an artificial neural network predicts beauty: Towards a model of processing-based aesthetics.

Generations of scientists have pursued the goal of defining beauty. While early scientists initially focused on objective criteria of beauty ('feature-based aesthetics'), philosophers and artists alike have since proposed that beauty arises from the interaction between the object and the individual who perceives it. The aesthetic theory of fluency formalizes this idea of interaction by proposing that beauty is determined by the efficiency of information processing in the perceiver's brain ('processing-based aesthetics'), and that efficient processing induces a positive aesthetic experience. The theory is supported by numerous psychological results, however, to date there is no quantitative predictive model to test it on a large scale. In this work, we propose to leverage the capacity of deep convolutional neural networks (DCNN) to model the processing of information in the brain by studying the link between beauty and neuronal sparsity, a measure of information processing efficiency. Whether analyzing pictures of faces, figurative or abstract art paintings, neuronal sparsity explains up to 28% of variance in beauty scores, and up to 47% when combined with a feature-based metric. However, we also found that sparsity is either positively or negatively correlated with beauty across the multiple layers of the DCNN. Our quantitative model stresses the importance of considering how information is processed, in addition to the content of that information, when predicting beauty, but also suggests an unexpectedly complex relationship between fluency and beauty.

Modular brain network in volitional eyes closing: enhanced integration with a marked impact on hubs.

Volitional eyes closing would shift brain's information processing modes from the "exteroceptive" to "interoceptive" state. This transition induced by the eyes closing is underpinned by a large-scale reconfiguration of brain network, which is still not fully comprehended. Here, we investigated the eyes-closing-relevant network reconfiguration by examining the functional integration among intrinsic modules. Our investigation utilized a publicly available dataset with 48 subjects being scanned in both eyes closed and eyes open conditions. It was found that the modular integration was significantly enhanced during the eyes closing, including lower modularity index, higher participation coefficient, less provincial hubs, and more connector hubs. Moreover, the eyes-closing-enhanced integration was particularly noticeable in the hubs of network, mainly located in the default-mode network. Finally, the hub-dominant modular enhancement was positively correlated to the eyes-closing-reduced entropy of BOLD signal, suggesting a close connection to the diminished consciousness of individuals. Collectively, our findings strongly suggested that the enhanced modular integration with substantially reorganized hubs characterized the large-scale cortical underpinning of the volitional eyes closing.

A Review of the Impacts of Music and Implications for Music Medicine

Music operates as a stimulus that arouses people’s emotions and induces the release of neurotransmitters and hormones in the brain such as serotonin and dopamine. As such, music has many physiological effects including increased heart rate, blood pressure, and respiratory rate as well as impacts on mood. It also activates many networks in the brain, such as auditory neural pathways that process music and sensory circuits. Research has shown that involvement in musical activities have a noticeable impact on the intellectual, social, and personal development of children, catalyzing cortical reorganization and permanently altering how the brain processes information. Engagement in music learning and training, in particular, has been found to impact cognitive function and development. Though research has been conducted on these impacts, there has been little research comparing the impacts of listening to music on young adult musicians and non-musicians. Future research should investigate what these differences are to help inform the use of music medicine on patients of varying degrees of past and present engagement in music training and play.

Activation network improves spatiotemporal modelling of human brain communication processes

Dynamic functional networks (DFN) have considerably advanced modelling of the brain communication processes. The prevailing implementation capitalizes on the system and network-level correlations between time series. However, this approach does not account for the continuous impact of non-dynamic dependencies within the statistical correlation, resulting in relatively stable connectivity patterns of DFN over time with limited sensitivity for communication dynamic between brain regions. Here, we propose an activation network framework based on the activity of functional connectivity (AFC) to extract new types of connectivity patterns during brain communication process. The AFC captures potential time-specific fluctuations associated with the brain communication processes by eliminating the non-dynamic dependency of the statistical correlation. In a simulation study, the positive correlation (r=0.966,p<0.001) between the extracted dynamic dependencies and the simulated "ground truth" validates the method's dynamic detection capability. Applying to autism spectrum disorders (ASD) and COVID-19 datasets, the proposed activation network extracts richer topological reorganization information, which is largely invisible to the DFN. Detailed, the activation network exhibits significant inter-regional connections between function-specific subnetworks and reconfigures more efficiently in the temporal dimension. Furthermore, the DFN fails to distinguish between patients and healthy controls. However, the proposed method reveals a significant decrease (p<0.05) in brain information processing abilities in patients. Finally, combining two types of networks successfully classifies ASD (83.636 % ± 11.969 %,mean±std) and COVID-19 (67.333 % ± 5.398 %). These findings suggest the proposed method could be a potential analytic framework for elucidating the neural mechanism of brain dynamics.

The effects of object size on spatial orientation: an eye movement study.

The processing of visual information in the human brain is divided into two streams, namely, the dorsal and ventral streams, object identification is related to the ventral stream and motion processing is related to the dorsal stream. Object identification is interconnected with motion processing, object size was found to affect the information processing of motion characteristics in uniform linear motion. However, whether the object size affects the spatial orientation is still unknown. Thirty-eight college students were recruited to participate in an experiment based on the spatial visualization dynamic test. Eyelink 1,000 Plus was used to collect eye movement data. The final direction difference (the difference between the final moving direction of the target and the final direction of the moving target pointing to the destination point), rotation angle (the rotation angle of the knob from the start of the target movement to the moment of key pressing) and eye movement indices under conditions of different object sizes and motion velocities were compared. The final direction difference and rotation angle under the condition of a 2.29°-diameter moving target and a 0.76°-diameter destination point were significantly smaller than those under the other conditions (a 0.76°-diameter moving target and a 0.76°-diameter destination point; a 0.76°-diameter moving target and a 2.29°-diameter destination point). The average pupil size under the condition of a 2.29°-diameter moving target and a 0.76°-diameter destination point was significantly larger than the average pupil size under other conditions (a 0.76°-diameter moving target and a 0.76°-diameter destination point; a 0.76°-diameter moving target and a 2.29°-diameter destination point). A relatively large moving target can resist the landmark attraction effect in spatial orientation, and the influence of object size on spatial orientation may originate from differences in cognitive resource consumption. The present study enriches the interaction theory of the processing of object characteristics and motion characteristics and provides new ideas for the application of eye movement technology in the examination of spatial orientation ability.

Pressure Pulsatility Links Cardio-Respiratory and Brain Rhythmicity.

This article presents evidence indicating that intracranial pressure (ICP) pulsatility, associated with the heartbeat and breathing, is not just a source of mechanical artefact in electrical recordings, but is "sensed" and plays a role in the brain's information processing. Patch-clamp recording of pressure-activated channels, and detection of Piezo2-protein channel expression in brain neurons, suggest that these channels provide neurons with an intrinsic resonance to ICP pulsatility, which acts to synchronize remote neural networks. Direct measurements in human patients indicate that heartbeat and breathing rhythms generate intracranial forces of tens of millinewtons, exceeding by orders of magnitude the localized forces shown by atomic force microscopy and optical tweezers to activate Piezo channels in isolated neocortical and hippocampal neurons. Additionally, many human touch and proprioceptors, which are also transduced by Piezo channels, show spiking that is phase-locked to heartbeat- and breathing-induced extracranial pressure pulsations. Finally, based on the observation that low-frequency oscillations modulate the phase and amplitude of high-frequency oscillations, body and brain oscillations are proposed to form a single hierarchical system in which the heartbeat is the basic frequency and scaling factor for all other oscillations. Together, these results support the idea that ICP pulsatility may be elemental in modulating the brain's electrical rhythmicity.

Complex Synaptic and Intrinsic Interactions Disrupt Input/Output Functions in the Hippocampus of Scn1b Knock-Out Mice.

Pathogenic variants in SCN1B have been linked to severe developmental epileptic encephalopathies including Dravet syndrome. Scn1b knock-out (KO) mice model SCN1B loss-of-function (LOF) disorders, demonstrating seizures, developmental delays, and early death. SCN1B encodes the protein β1, an ion channel auxiliary subunit that also has roles in cell adhesion, neurite outgrowth, and gene expression. The goal of this project is to better understand of how loss of Scn1b alters information processing in the brain, resulting in seizures and associated cognitive dysfunction. Using slice electrophysiology in the CA1 region of the hippocampus from male and female Scn1b KO mice and wild-type (WT) littermates, we found that processing of physiologically relevant patterned Schaffer collateral (SC) stimulation produces larger, prolonged depolarizations and increased spiking in KO neurons compared with WTs. KO neurons exhibit enhanced intrinsic excitability, firing more action potentials with current injection. Interestingly, SC stimulation produces smaller, more facilitating excitatory and IPSCs in KO pyramidal neurons, but larger postsynaptic potentials (PSPs) with the same stimulation. We also found reduced intrinsic firing of parvalbumin (PV)-expressing interneurons and disrupted recruitment of both parvalbumin-expressing and somatostatin (SST)-expressing interneurons in response to patterned synaptic stimulation. Neuronal information processing relies on the interplay between synaptic properties, intrinsic properties that amplify or suppress incoming synaptic signals, and firing properties that produce cellular output. We found changes at each of these levels in Scn1b KO pyramidal neurons, resulting in fundamentally altered cellular information processing in the hippocampus that likely contributes to the complex phenotypes of SCN1B-linked epileptic encephalopathies.SIGNIFICANCE STATEMENT Genetic developmental epileptic encephalopathies have limited treatment options, in part because of our lack of understanding of how genetic changes result in dysfunction at the cellular and circuit levels. SCN1B is a gene linked to Dravet syndrome and other developmental epileptic encephalopathies, and Scn1b knock-out (KO) mice phenocopy the human disease, allowing us to study underlying neurophysiological changes. Here, we found changes at all levels of neuronal information processing in brains lacking Scn1b, including intrinsic excitability, synaptic properties, and synaptic integration, resulting in greatly enhanced input/output functions of the hippocampus. Our study shows that loss of Scn1b results in a complex array of cellular and network changes that fundamentally alters information processing in the hippocampus.

Experiences of interpersonal victimization and abuse among autistic people.

What do we already know?Autistic people are more likely to have negative life experiences than non-autistic people, from bullying and ostracization, to being victims of crime, to unemployment and homelessness. This includes being victims of intimate partner violence, sexual assault and domestic abuse. Quantitative work has suggested that as many as 90% of autistic people experience these forms of abuse in some form during their lives, but there is little work asking them to talk about harmful relationships in their own words.What does this article add?This article reports on interviews with 24 autistic adults about their experiences of being victims of intimate partner violence, sexual assault and/or domestic abuse. Some of the themes which came from these interviews are shared with non-autistic victims, but others appeared unique to autistic people. One of these was evidence for unique autism-related vulnerabilities, as well as the impact the abuse had on their relationships long term. Participants also talked about how the sex and relationship education they had received had inadequately prepared them for adult relationships, and how this had contributed to their struggle to recognize and react to abusive behaviour.Implications for practice, research and policyPolicies around intimate partner violence and sexual assault need to be updated to account for the different ways in which neurodivergent people (people whose brains process information differently from the majority) may discuss their experiences, rather than looking for 'standard narratives' as an indicator of a need for support. Relationship and sex education should be tailored for autistic young people to help them recognize abusive behaviours, and include how to respond to these safely. We recommend that future research tries to focus specifically on the abuse experiences of autistic men, non-binary and trans people, who have been under-represented in studies to date. In addition, much less is known about the abuse experiences of autistic people of colour or autistic people with intellectual disabilities, who also need to be actively included in these discussions.