Bidirectional lexical-gustatory synesthesia

In developmental lexical–gustatory synesthesia, specific words (inducers) can trigger taste perceptions (concurrents) and these synesthetic associations are generally stable. We describe a case of multilingual lexical–gustatory synesthesia for whom some synesthesias were bidirectional as some tastes also triggered auditory word associations. Evoked concurrents could be gustatory but also tactile sensations. In addition to words and pseudowords, many voices were effective inducers, suggesting increased connections between cortical taste areas and both voice-selective and language-selective areas. Lasting changes in some evoked tastes occurred during childhood suggesting that some plasticity can be present after the initial learning of associations. Inducers were often linked to taste concurrents phonologically or semantically, but also through identifiable childhood episodes (persons or events). Several inducers were phonologically linked to episodic inducers suggesting a process of secondary acquisition for many inducers. Implications of these observations are discussed.     

Role of cerebellum in fine speech control in childhood: persistent dysarthria after surgical treatment for posterior fossa tumour

Dysarthria following surgical resection of childhood posterior fossa tumour (PFT) is most commonly documented in a select group of participants with mutism in the acute recovery phase, thus limiting knowledge of post-operative prognosis for this population of children as a whole. Here we report on the speech characteristics of 13 cases seen long-term after surgical treatment for childhood PFT, unselected for the presence of post-operative mutism (mean time post-surgery = 6y10 m, range 1;4-12;6 years, two had post-operative mutism), and examine factors affecting outcome. Twenty-six age- and sex- matched healthy controls were recruited for comparison. Participants in both groups had speech assessments using detailed perceptual and acoustic methods. Over two-thirds of the group (69%) with removal of PFT had a profile of typically mild dysarthria. Prominent speech deficits included consonant imprecision, reduced rate, monopitch and monoloudness. We conclude that speech deficits may persist even up to 10 years post-surgery in participants who have not shown mutism in the acute phase. Of cases with unilateral lesions, poorer outcomes were associated with right cerebellar tumours compared to left, consistent with the notion based on adult data that speech is controlled by reciprocal right cerebellar/left frontal interactions. These results confirm the important role of the cerebellum in the control of fine speech movements in children.     

Conduction aphasia, sensory-motor integration, and phonological short-term memory - an aggregate analysis of lesion and fMRI data

Conduction aphasia is a language disorder characterized by frequent speech errors, impaired verbatim repetition, a deficit in phonological short-term memory, and naming difficulties in the presence of otherwise fluent and grammatical speech output. While traditional models of conduction aphasia have typically implicated white matter pathways, recent advances in lesions reconstruction methodology applied to groups of patients have implicated left temporoparietal zones. Parallel work using functional magnetic resonance imaging (fMRI) has pinpointed a region in the posterior most portion of the left planum temporale, area Spt, which is critical for phonological working memory. Here we show that the region of maximal lesion overlap in a sample of 14 patients with conduction aphasia perfectly circumscribes area Spt, as defined in an aggregate fMRI analysis of 105 subjects performing a phonological working memory task. We provide a review of the evidence supporting the idea that Spt is an interface site for the integration of sensory and vocal tract-related motor representations of complex sound sequences, such as speech and music and show how the symptoms of conduction aphasia can be explained by damage to this system.     

Differential prefrontal–temporal neural correlates of semantic processing in children

This study used functional magnetic resonance imaging (fMRI) to examine brain–behavior correlations in a group of 16 children (9- to 12-year-olds). Activation was measured during a semantic judgment task presented in either the visual or auditory modality that required the individual to determine whether a final word was related in meaning to one of two previous words (e.g., found–tank–lost). The main finding was that higher performers (i.e., accuracy) were associated with more activation in posterior representational systems including the inferior and middle temporal gyri, whereas lower performers were associated with more activation in anterior regions including the inferior and middle frontal gyri. This pattern of results was interpreted as reflecting an elaborated semantic representational system in temporal areas for the high accuracy performers that allowed them to efficiently and accurately make meaning based judgments. The low accuracy performers may have an inaccurate or weakly interconnected semantic system that results in greater use of frontal areas in a feature selection process.     

Age-dependent variability in spatiotemporal gait parameters and the walk-to-run transition

Adolescents tend to exhibit more variability in their gait patterns than adults, suggesting a lack of gait maturity during this period of ongoing musculoskeletal growth and development. However, there is a lack of consensus over the age at which mature gait patterns are achieved and the factors contributing to gait maturation. Therefore, the purpose of this study was to investigate gait control and maturity in adolescents by determining if differences existed between adolescents and adults in a) the amount of spatiotemporal variability of walking and running patterns across a range of speeds, and b) how swiftly gait patterns are adapted to increasing gait speed during the walk-to-run transition. Forty-six adolescents (10–12-year-olds, n = 17; 13–14-year-olds, n = 12; and 15–17-year-olds, n = 17) and 12 young adults completed an incrementally ramped treadmill test (+0.2 km·h⁻¹ every 30 s) to determine the preferred transition speed (PTS) during a walk-to-run transition. Age-related differences in the variability of stride lengths and stride durations were assessed across 4 speeds (self-selected walking speed, PTS − 0.06 m·s⁻¹, PTS + 0.06 m·s⁻¹, PTS + 0.83 m·s⁻¹). Repeated measures ANOVAs (p < 0.05) compared coefficients of variation for these spatiotemporal parameters, while a one-way ANOVA compared the numbers of gait transitions and speed increments used to identify PTS between the adolescent groups and young adults. Compared to adults, 10–12yo exhibited more spatiotemporal variability during all gait conditions, while 13–17yo only exhibited more variability at PTS + 0.06 m·s⁻¹. No age-dependent pattern was observed in PTS values, but 10–12yo completed more gait transitions over more speed increments than 15–17yo and adults. The development of mature gait patterns is thus a progressive process, with walking maturing at an earlier age than running. As 10-12yo were unable to swiftly adapt gait patterns to the changing task demands, their control mechanisms of gait may not have fully matured yet.     

Convolutional neural network based Alzheimer’s disease classification from magnetic resonance brain images

Alzheimer’s disease, the most common form of dementia is a neurodegenerative brain order that has currently no cure for it. Hence, early diagnosis of such disease using computer-aided systems is a subject of great importance and extensive research amongst researchers. Nowadays, deep learning or particularly convolutional neural network (CNN) is getting more attention due to its state-of-the-art performances in variety of computer vision tasks such as visual object classification, detection and segmentation. Several recent studies, that have used brain MRI scans and deep learning have shown promising results for diagnosis of Alzheimer’s disease. However, most common issue with deep learning architectures such as CNN is that they require large amount of data for training. In this paper, a mathematical model P_FS_EC_TL based on transfer learning is used in which a CNN architecture, VGG-16 trained on ImageNet dataset is used as a feature extractor for the classification task. Experimentation is performed on data collected from Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The accuracy of the 3-way classification using the described method is 95.73% for the validation set.     

Dissociable patterns of brain activity during comprehension of rapid and syntactically complex speech: evidence from fMRI

Sentence comprehension is a complex task that involves both language-specific processing components and general cognitive resources. Comprehension can be made more difficult by increasing the syntactic complexity or the presentation rate of a sentence, but it is unclear whether the same neural mechanism underlies both of these effects. In the current study, we used event-related functional magnetic resonance imaging (fMRI) to monitor neural activity while participants heard sentences containing a subject-relative or object-relative center-embedded clause presented at three different speech rates. Syntactically complex object-relative sentences activated left inferior frontal cortex across presentation rates, whereas sentences presented at a rapid rate recruited frontal brain regions such as anterior cingulate and premotor cortex, regardless of syntactic complexity. These results suggest that dissociable components of a large-scale neural network support the processing of syntactic complexity and speech presented at a rapid rate during auditory sentence processing.     

Bilateral facilitation of motor control in chronic hemiplegia

The present study addressed the efficacy of concurrently moving both arms, with and without a load added to the uninvolved arm, in facilitating the quality of movement of the involved side in individuals with moderate, chronic hemiplegia. Six hemiplegic cerebrovascular accident (CVA) subjects with left-hemisphere lesions participated in the study. The four males and two females ranged from 46 to 77 years of age and 30–96 months post-CVA. All subjects scored at least 70% on the Fugl-Meyer test of motor function. The task was to perform discrete unilateral and bilateral elbow extensions in the horizontal plane. The movements were 45° in amplitude and were to terminate in a 10° target zone that was indicated by an illustration of a coffee mug. The instructions were to move toward the mug as smoothly as possible in a movement time (MT) determined to be 20% longer than their minimal MT for that distance. The primary dependent variable was the percentage of continuous vs. discontinuous trajectories observed in each condition, based on whether or not a transient hesitation or reversal was observed. Phase of peak velocity was also quantified as a general indication of the symmetry of the velocity profile. Three of the six subjects exhibited a greater percentage of continuous movements of the involved arm in the nonloaded bilateral condition than the unimanual condition. Five subjects benefited when the uninvolved arm was inertially loaded in the bilateral condition when compared with unimanual performance. Only the oldest subject failed to exhibit facilitation. Peak velocity phase tended to normalize toward symmetry in the bilateral conditions. These findings are consistent with prior evidence that the control of the involved arm improves during bimanual performance for some hemiplegic subjects. It further suggests loading the uninvolved arm may benefit some subjects with respect to unimanual performance, with age perhaps playing a role in determining efficacy.     

The brain generates its own sentence melody: a Gestalt phenomenon in speech perception

Brain processes underlying spoken language comprehension comprise auditory encoding, prosodic analysis and linguistic evaluation. Auditory encoding usually activates both hemispheres while language-specific stages are lateralized: analysis of prosodic cues are right-lateralized while linguistic evaluation is left-lateralized. Here, we investigated to what extent the absence of prosodic information influences lateralization. MEG brain-responses indicated that syntactic violations lead to early bi-lateral brain responses for syntax violations. When the pitch of sentences was flattened to diminish prosodic cues, the brain's syntax response was lateralized to the right hemisphere, indicating that the missing pitch was generated automatically by the brain when it was absent. This represents a Gestalt phenomenon, since we perceive more than is actually presented.     

Exploring the effects of EEG signals on collision cases happening in the process of young drivers’ braking

Detecting mental states in drivers offers an opportunity to reduce accidents by triggering alerts and signaling the need for rest or renewed focus. Here we used electroencephalography (EEG) to measure brain signals in young drivers operating a driving simulator to detect mental states and predict accidents. We measured reaction times to unexpected hazardous events and correlated them with EEG signals measured from the frontal, parietal, and temporal cortices as well as the central sulcus (corresponding to motor cortex). We found that EEG signals in the relative beta (power in beta (13–30 Hz) relative to total power of the EEG (0.5–30 Hz)), alpha/delta, alpha/theta, beta/delta, beta/theta frequency bands were higher for collisions than successful collision avoidance, and that the key decision-making period is the 2nd second before braking. Importantly, a decision tree classifier trained on these neural signals predicted collision avoidance outcomes. Then based on random forest model, we extracted three critical neural signals (beta/delta_frontal, relative beta_parietal and relative beta_central Sulcus) to classify collision avoidance outcomes. Our findings suggest measuring EEG during driving may provide useful signals for enhancing driver safety.