Neural processing of speech comprehension in noise predicts individual age using fNIRS-based brain-behavior models.

Speech comprehension in noise depends on complex interactions between peripheral sensory and central cognitive systems. Despite having normal peripheral hearing, older adults show difficulties in speech comprehension. It remains unclear whether the brain's neural responses could indicate aging. The current study examined whether individual brain activation during speech perception in different listening environments could predict age. We applied functional near-infrared spectroscopy to 93 normal-hearing human adults (20 to 70 years old) during a sentence listening task, which contained a quiet condition and 4 different signal-to-noise ratios (SNR = 10, 5, 0, -5 dB) noisy conditions. A data-driven approach, the region-based brain-age predictive modeling was adopted. We observed a significant behavioral decrease with age under the 4 noisy conditions, but not under the quiet condition. Brain activations in SNR = 10 dB listening condition could successfully predict individual's age. Moreover, we found that the bilateral visual sensory cortex, left dorsal speech pathway, left cerebellum, right temporal-parietal junction area, right homolog Wernicke's area, and right middle temporal gyrus contributed most to prediction performance. These results demonstrate that the activations of regions about sensory-motor mapping of sound, especially in noisy conditions, could be sensitive measures for age prediction than external behavior measures.

Exploring the clinical diagnostic value of linguistic learning ability in patients with disorders of consciousness using electrooculography.

For patients with disorders of consciousness (DoC), accurate assessment of residual consciousness levels and cognitive abilities is critical for developing appropriate rehabilitation interventions. In this study, we investigated the potential of electrooculography (EOG) in assessing language processing abilities and consciousness levels. Patients' EOG data and related electrophysiological data were analysed before and after explicit language learning. The results showed distinct differences in vocabulary learning patterns among patients with varying levels of consciousness. While minimally conscious patients showed significant neural tracking of artificial words and notable learning effects similar to those observed in healthy controls, whereas patients with unresponsive wakefulness syndrome did not show such effects. Correlation analysis further indicated that EOG detected vocabulary learning effects with comparable validity to electroencephalography, reinforcing the credibility of EOG indicator as a diagnostic tool. Critically, EOG also revealed significant correlations between individual patients' linguistic learning performance and their Oromotor/verbal function as assessed through behavioural scales. In conclusion, this study explored the differences in language processing abilities among patients with varying consciousness levels. By demonstrating the utility of EOG in evaluating consciousness and detecting vocabulary learning effects, as well as its potential to guide personalised rehabilitation, our findings indicate that EOG indicators show promise as a rapid, accurate and effective additional tool for diagnosing and managing patients with DoC.

Dissociation between frontal and temporal-parietal contributions to connected speech in acute stroke.

Humans are uniquely able to retrieve and combine words into syntactic structure to produce connected speech. Previous identification of focal brain regions necessary for production focused primarily on associations with the content produced by speakers with chronic stroke, where function may have shifted to other regions after reorganization occurred. Here, we relate patterns of brain damage with deficits to the content and structure of spontaneous connected speech in 52 speakers during the acute stage of a left hemisphere stroke. Multivariate lesion behaviour mapping demonstrated that damage to temporal-parietal regions impacted the ability to retrieve words and produce them within increasingly complex combinations. Damage primarily to inferior frontal cortex affected the production of syntactically accurate structure. In contrast to previous work, functional-anatomical dissociations did not depend on lesion size likely because acute lesions were smaller than typically found in chronic stroke. These results are consistent with predictions from theoretical models based primarily on evidence from language comprehension and highlight the importance of investigating individual differences in brain-language relationships in speakers with acute stroke.

White matter basis for the hub-and-spoke semantic representation: evidence from semantic dementia.

The hub-and-spoke semantic representation theory posits that semantic knowledge is processed in a neural network, which contains an amodal hub, the sensorimotor modality-specific regions, and the connections between them. The exact neural basis of the hub, regions and connectivity remains unclear. Semantic dementia could be an ideal lesion model to construct the semantic network as this disease presents both amodal and modality-specific semantic processing (e.g. colour) deficits. The goal of the present study was to identify, using an unbiased data-driven approach, the semantic hub and its general and modality-specific semantic white matter connections by investigating the relationship between the lesion degree of the network and the severity of semantic deficits in 33 patients with semantic dementia. Data of diffusion-weighted imaging and behavioural performance in processing knowledge of general semantic and six sensorimotor modalities (i.e. object form, colour, motion, sound, manipulation and function) were collected from each subject. Specifically, to identify the semantic hub, we mapped the white matter nodal degree value (a graph theoretical index) of the 90 regions in the automated anatomical labelling atlas with the general semantic abilities of the patients. Of the regions, only the left fusiform gyrus was identified as the hub because its structural connectivity strength (i.e. nodal degree value) could significantly predict the general semantic processing of the patients. To identify the general and modality-specific semantic connections of the semantic hub, we separately correlated the white matter integrity values of each tract connected with the left fusiform gyrus, with the performance for general semantic processing and each of six semantic modality processing. The results showed that the hub region worked in concert with nine other regions in the semantic memory network for general semantic processing. Moreover, the connection between the hub and the left calcarine was associated with colour-specific semantic processing. The observed effects could not be accounted for by potential confounding variables (e.g. total grey matter volume, regional grey matter volume and performance on non-semantic control tasks). Our findings refine the neuroanatomical structure of the semantic network and underline the critical role of the left fusiform gyrus and its connectivity in the network.

White matter networks dissociate semantic control from semantic knowledge representations: Evidence from voxel-based lesion-symptom mapping.

Although semantic system is composed of two distinctive processes (i.e., semantic knowledge and semantic control), it remains unknown in which way these two processes dissociate from each other. Investigating the white matter neuroanatomy underlying these processes helps improve understanding of this question. To address this issue, we recruited brain-damaged patients with semantic dementia (SD) and semantic aphasia (SA), who had selective predominant deficits in semantic knowledge and semantic control, respectively. We built regression models to identify the white matter network associated with the semantic performance of each patient group. Semantic knowledge deficits in the SD patients were associated with damage to the left medial temporal network, while semantic control deficits in the SA patients were associated with damage to the other two networks (left frontal-temporal/occipital and frontal-subcortical networks). The further voxel-based analysis revealed additional semantic-relevant white matter tracts. These findings specify different processing principles of the components in semantic system.

Left Anterior Temporal Lobe and Bilateral Anterior Cingulate Cortex Are Semantic Hub Regions: Evidence from Behavior-Nodal Degree Mapping in Brain-Damaged Patients.

The organizational principles of semantic memory in the human brain are still controversial. Although studies have shown that the semantic system contains hub regions that bind information from different sensorimotoric modalities to form concepts, it is unknown whether there are hub regions other than the anterior temporal lobe (ATL). Meanwhile, previous studies have rarely used network measurements to explore the hubs or correlated network indexes with semantic performance, although the most direct supportive evidence of hubs should come from the network perspective. To fill this gap, we correlated the brain-network index with semantic performance in 86 brain-damaged patients. We especially selected the nodal degree measure that reflects how well a node is connected in the network. The measure was calculated as the total number of connections of a given node with other nodes in the resting-state functional MRI network. Semantic ability was measured using the performance of both general and modality-specific (object form, color, motion, sound, manipulation, and function) semantic tasks. We found that the left ATL and the bilateral anterior cingulate cortex could be semantic hubs because the reduced nodal degree values of these regions could effectively predict the deficits in both general and modality-specific semantic performance. Moreover, the effects remained when the analyses were performed only in the patients who did not have lesions in these regions. The two hub regions might support semantic representations and executive control processes, respectively. These data provide empirical evidence for the distributed-plus-hub theory of semantic memory from the network perspective. SIGNIFICANCE STATEMENT: Although the distributed-plus-hub organization of semantic memory has been proposed for several years, it remains unclear which hubs other than the anterior temporal lobe are included in the semantic system. Here, we identified such hubs from an innovative network perspective. The voxelwise nodal degree values were correlated with the performance of general and modality-specific semantic tasks in 86 patients with brain damage. We observed that the left anterior temporal lobe and bilateral anterior cingulate cortex could be semantic hubs because their decreased nodal degree values were significantly correlated with the severity of the deficit in semantic performance. The two hub regions might contribute to semantic representational and control processes, respectively. These findings offer new evidence for the distributed-plus-hub theory.

Resolving power of diffraction imaging with an objective: a numerical study.

Diffraction imaging in the far-field can detect 3D morphological features of an object for its coherent nature. We describe methods for accurate calculation and analysis of diffraction images of scatterers of single and double spheres by an imaging unit based on microscope objective at non-conjugate positions. A quantitative study of the calculated diffraction imaging in spectral domain has been performed to assess the resolving power of diffraction imaging. It has been shown numerically that with coherent illumination of 532 nm in wavelength the imaging unit can resolve single spheres of 2 µm or larger in diameters and double spheres separated by less than 300 nm between their centers.

Realistic optical cell modeling and diffraction imaging simulation for study of optical and morphological parameters of nucleus.

Coherent light scattering presents complex spatial patterns that depend on morphological and molecular features of biological cells. We present a numerical approach to establish realistic optical cell models for generating virtual cells and accurate simulation of diffraction images that are comparable to measured data of prostate cells. With a contourlet transform algorithm, it has been shown that the simulated images and extracted parameters can be used to distinguish virtual cells of different nuclear volumes and refractive indices against the orientation variation. These results demonstrate significance of the new approach for development of rapid cell assay methods through diffraction imaging.

Spectrophotometric determination of turbid optical parameters without using an integrating sphere.

Spectrophotometric quantification of turbidity by multiple optical parameters has wide-ranging applications in material analysis and life sciences. A robust system design needs to combine hardware for precise measurement of light signals with software to accurately model measurement configuration and rapidly solve a sequence of challenging inverse problems. We have developed and validated a design approach and performed system validation based on radiative transfer theory for determination of absorption coefficient, scattering coefficient, and anisotropy factor without using an integrating sphere. Accurate and rapid determination of parameters and spectra is achieved for microsphere suspension samples by combining photodiode-based measurement of four signals with the Monte Carlo simulation and perturbation-based inverse calculations. The three parameters of microsphere suspension samples have been determined from the measured signals as functions of wavelength from 400 to 800 nm and agree with calculated results based on the Mie theory. It has been shown that the inverse problems in the cases of microsphere suspension samples are well posed with convex cost functions to yield unique solutions, and it takes about 1 min to obtain the three parameters per wavelength.

Advances in semantic dementia: Neuropsychology, pathology & neuroimaging.

Semantic dementia is a kind of neurodegenerative disorder, characterized by prominent semantic impairments and anterior temporal lobe atrophy. Since 2010, more studies have devoted to this rare disorder, revealing that it is more complex than we think. Clinical advances include more specific findings of semantic impairments and other higher order cognitive deficits. Neuroimaging techniques can help revealing the different brain networks affected (both structurally and functionally) in this condition. Pathological and genetic studies have also found more complex situations of semantic dementia, which might explain the huge variance existing in semantic dementia. Moreover, the current diagnosis criteria mainly focus on semantic dementia's classical prototype. We further delineated the features of three subtypes of semantic dementia based on atrophy lateralization with three severity stages. In a broader background, as a part of the continuum of neurodegenerative disorders, semantic dementia is commonly compared with other resembling conditions. Therefore, we summarized the differential diagnosis between semantic dementia and them. Finally, we introduced the challenges and achievements of its diagnosis, treatment, care and cross cultural comparison. By providing a comprehensive picture of semantic dementia on different aspects of advances, we hope to deepen the understanding of semantic dementia and promote more inspirations on both clinical and theoretical studies about it.

Correction: Horne et al. White Matter Correlates of Domain-Specific Working Memory. Brain Sci. 2023, 13, 19.

In the original publication [...].

White matter network underlying semantic processing: evidence from stroke patients.

The hub-and-spoke theory of semantic representation fractionates the neural underpinning of semantic knowledge into two essential components: the sensorimotor modality-specific regions and a crucially important semantic hub region. Our previous study in patients with semantic dementia has found that the hub region is located in the left fusiform gyrus. However, because this region is located within the brain damage in patients with semantic dementia, it is not clear whether the semantic deficit is caused by structural damage to the hub region itself or by its disconnection from other brain regions. Stroke patients do not have any damage to the left fusiform gyrus, but exhibit amodal and modality-specific deficits in semantic processing. Therefore, in this study, we validated the semantic hub region from a brain network perspective in 79 stroke patients and explored the white matter connections associated with it. First, we collected data of diffusion-weighted imaging and behavioural performance on general semantic tasks and modality-specific semantic tasks (assessing object knowledge on form, colour, motion, sound, manipulation and function). We then used correlation and regression analyses to examine the association between the nodal degree values of brain regions in the whole-brain structural network and general semantic performance in the stroke patients. The results revealed that the connectivity of the left fusiform gyrus significantly predicted general semantic performance, indicating that this region is the semantic hub. To identify the semantic-relevant connections of the semantic hub, we then correlated the white matter integrity values of each tract connected to the left fusiform gyrus separately with performance on general and modality-specific semantic processing. We found that the hub region accomplished general semantic processing through white matter connections with the left superior temporal pole, middle temporal gyrus, inferior temporal gyrus and hippocampus. The connectivity between the hub region and the left hippocampus, superior temporal pole, middle temporal gyrus, inferior temporal gyrus and parahippocampal gyrus was differentially involved in object form, colour, motion, sound, manipulation and function processing. After statistically removing the effects of potential confounding variables (i.e. whole-brain lesion volume, lesion volume of regions of interest and performance on non-semantic control tasks), the observed effects remained significant. Together, our findings support the role of the left fusiform gyrus as a semantic hub region in stroke patients and reveal its crucial connectivity in the network. This study provides new insights and evidence for the neuroanatomical organization of semantic memory in the human brain.

Phase synchronization during the processing of taxonomic and thematic relations.

Semantic relations include "taxonomic" relations based on shared features and "thematic" relations based on co-occurrence in events. The "dual-hub" account proposes that the anterior temporal lobe (ATL) is functionally specialized for taxonomic relations and the inferior parietal lobule (IPL) for thematic relations. This study examined this claim by analyzing the intra- and inter-region phase synchronization of intracranial EEG data from electrodes in the ATL, IPL, and two subregions of the semantic control network: left inferior frontal gyrus (IFG) and posterior middle temporal gyrus (pMTG). Ten participants with epilepsy completed a semantic relatedness judgment task during intracranial EEG recording and had electrodes in at least one hub and at least one semantic control region. Theta band phase synchronization was partially consistent with the dual-hub account: synchronization between the ATL and IFG/pMTG increased when processing taxonomic relations, and synchronization within the IPL and between IPL and pMTG increased when processing thematic relations.

Recovery of Verbal Working Memory Depends on Left Hemisphere White Matter Tracts.

Researchers propose that the recovery of language function following stroke depends on the recruitment of perilesional regions in the left hemisphere and/or homologous regions in the right hemisphere (Kiran, 2012). Many investigations of recovery focus on changes in gray matter regions (e.g., Turkeltaub et al., 2011), whereas relatively few examine white matter tracts (e.g., Schlaug et al., 2009) and none address the role of these tracts in the recovery of verbal working memory (WM). The present study addressed these gaps, examining the role of left vs. right hemisphere tracts in the longitudinal recovery of phonological and semantic WM. For 24 individuals with left hemisphere stroke, we assessed WM performance within one week of stroke (acute timepoint) and at more than six months after stroke (chronic timepoint). To address whether recovery depends on the recruitment of left or right hemisphere tracts, we assessed whether changes in WM were related to the integrity of five white matter tracts in the left hemisphere which had been implicated previously in verbal WM and their right hemisphere analogues. Behavioral results showed significant improvement in semantic but not phonological WM from the acute to chronic timepoints. Improvements in semantic WM significantly correlated with tract integrity as measured by functional anisotropy in the left direct segment of the arcuate fasciculus, inferior fronto-occipital fasciculus and inferior longitudinal fasciculus. The results confirm the role of white matter tracts in language recovery and support the involvement of the left rather than right hemisphere in the recovery of semantic WM.

Impaired discourse content in aphasia is associated with frontal white matter damage.

Aphasia is a common consequence of stroke with severe impacts on employability, social interactions and quality of life. Producing discourse-relevant information in a real-world setting is the most important aspect of recovery because it is critical to successful communication. This study sought to identify the lesion correlates of impaired production of relevant information in spoken discourse in a large, unselected sample of participants with post-stroke aphasia. Spoken discourse (n = 80) and structural brain scans (n = 66) from participants with aphasia following left hemisphere stroke were analysed. Each participant provided 10 samples of spoken discourse elicited in three different genres, and 'correct information unit' analysis was used to quantify the informativeness of speech samples. The lesion correlates were identified using multivariate lesion-symptom mapping, voxel-wise disconnection and tract-wise analyses. Amount and speed of relevant information were highly correlated across different genres and with total lesion size. The analyses of lesion correlates converged on the same pattern: impaired production of relevant information was associated with damage to anterior dorsal white matter pathways, specifically the arcuate fasciculus, frontal aslant tract and superior longitudinal fasciculus. Damage to these pathways may be a useful biomarker for impaired informative spoken discourse and informs development of neurorehabilitation strategies.

Anterior connectivity critical for recovery of connected speech after stroke.

Connected speech recovers to different degrees across people after left hemisphere stroke, but white matter predictors of differential recovery from the acute stage of stroke are unknown. We assessed changes in lexical-syntactic aspects of connected speech in a longitudinal analysis of 40 individuals (18 females) from the acute stage of left hemisphere stroke (within an average of 4 days post-stroke) to subacute (within 2 months) and chronic stages (early: 6 months, late: 1 year) while measuring the extent of acute lesions on white matter tracts to identify tracts predictive of recovery. We found that acute damage to the frontal aslant tract led to a decreased recovery of the fluency and structural complexity of connected speech during the year following left hemisphere stroke. The results were independent of baseline performance, overall lesion volume and the proportion of damage to tract-adjacent grey matter. This longitudinal analysis from acute to chronic stroke provides the first evidence that recovery of fluent and structurally complex spontaneous connected speech requires intact left frontal connectivity via the frontal aslant tract. That the frontal aslant tract was critical for recovery at early as well as later stages of stroke demonstrates that anterior connectivity plays a lasting and important role for the reorganization of function related to the successful production of connected speech.

White Matter Correlates of Domain-Specific Working Memory.

Prior evidence suggests domain-specific working memory (WM) buffers for maintaining phonological (i.e., speech sound) and semantic (i.e., meaning) information. The phonological WM buffer's proposed location is in the left supramarginal gyrus (SMG), whereas semantic WM has been related to the left inferior frontal gyrus (IFG), the middle frontal gyrus (MFG), and the angular gyrus (AG). However, less is known about the white matter correlates of phonological and semantic WM. We tested 45 individuals with left hemisphere brain damage on single word processing, phonological WM, and semantic WM tasks and obtained T1 and diffusion weighted neuroimaging. Virtual dissections were performed for each participants' arcuate fasciculus (AF), inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus (ILF), middle longitudinal fasciculus (MLF), and uncinate fasciculus (UF), which connect the proposed domain-specific WM buffers with perceptual or processing regions. The results showed that the left ILF, MLF, IFOF, and the direct segment of the AF were related to semantic WM performance. Phonological WM was related to both the left ILF and the MLF. This work informs our understanding of the white matter correlates of WM, especially semantic WM, which has not previously been investigated. In addition, this work helps to adjudicate between theories of verbal WM, providing some evidence for separate pathways supporting phonological and semantic WM.

Working Memory Capacities Neurally Dissociate: Evidence from Acute Stroke.

Substantial behavioral evidence implies the existence of separable working memory (WM) components for maintaining phonological and semantic information. In contrast, only a few studies have addressed the neural basis of phonological versus semantic WM using functional neuroimaging and none has used a lesion-symptom mapping (LSM) approach. Here, we address this gap, reporting a multivariate LSM study of phonological and semantic WM for 94 individuals at the acute stage of left hemisphere stroke. Testing at the acute stage avoids issues of brain reorganization and the adoption of patient strategies for task performance. The LSM analyses for each WM component controlled for the other WM component and semantic and phonological knowledge at the single word level. For phonological WM, the regions uncovered included the supramarginal gyrus, argued to be the site of phonological storage, and several cortical and subcortical regions plausibly related to inner rehearsal. For semantic WM, inferior frontal regions and the angular gyrus were uncovered. The findings thus provide converging evidence for separable systems for phonological and semantic WM that are distinguished from the systems supporting long-term knowledge representations in those domains.

A SURVEY ON THE USE OF DATA CLUSTERING FOR INTRUSION DETECTION SYSTEM IN CYBERSECURITY.

In the present world, it is difficult to realize any computing application working on a standalone computing device without connecting it to the network. A large amount of data is transferred over the network from one device to another. As networking is expanding, security is becoming a major concern. Therefore, it has become important to maintain a high level of security to ensure that a safe and secure connection is established among the devices. An intrusion detection system (IDS) is therefore used to differentiate between the legitimate and illegitimate activities on the system. There are different techniques are used for detecting intrusions in the intrusion detection system. This paper presents the different clustering techniques that have been implemented by different researchers in their relevant articles. This survey was carried out on 30 papers and it presents what different datasets were used by different researchers and what evaluation metrics were used to evaluate the performance of IDS. This paper also highlights the pros and cons of each clustering technique used for IDS, which can be used as a basis for future work.

The left inferior longitudinal fasciculus supports orthographic processing: Evidence from a lesion-behavior mapping analysis.

Orthographic processing is a critical stage in visual word recognition. However, the white-matter pathways that support this processing are unclear, as prior findings might have been confounded by impure behavioral measures, potential structural reorganization of the brain, and limited sample sizes. To address this issue, we investigated the correlations between the integrity of 20 major tracts in the whole brain and the pure orthographic index across 67 patients with short-term brain damage. The integrity of the tracts was measured by the lesion volume percentage and the mean fractional anisotropy value. The orthographic index was calculated as the residual of the orthographic tasks after regressing out corresponding nonorthographic tasks and the orthographic factor from the principal component analysis (PCA) on the basis of four orthographic tasks. We found significant correlations associated with the left inferior longitudinal fasciculus (ILF), even after controlling for the influence of potential confounding variables. These observations strengthen evidence for the vital role of the left ILF in orthographic processing.