Face recognition and memory in congenital amusia

Do developmental dyslexia and congenital amusia share underlying impairments?

Developmental dyslexia and congenital amusia have common characteristics. Yet, their possible association in some individuals has been addressed only scarcely. Recently, two converging studies reported a sizable comorbidity rate between these two neurodevelopmental disorders (Couvignou et al., Cognitive Neuropsychology 2019; Couvignou & Kolinsky, Neuropsychologia 2021). However, the reason for their association remains unclear. Here, we investigate the hypothesis of shared underlying impairments between dyslexia and amusia. Fifteen dyslexic children with amusia (DYS+A), 15 dyslexic children without amusia (DYS-A), and two groups of 25 typically developing children matched on either chronological age (CA) or reading level (RL) were assessed with a behavioral battery aiming to investigate phonological and pitch processing capacities at auditory memory, perceptual awareness, and attentional levels. Overall, our results suggest that poor auditory serial-order memory increases susceptibility to comorbidity between dyslexia and amusia and may play a role in the development of the comorbid phenotype. In contrast, the impairments observed in the DYS+A children for auditory item memory, perceptual awareness, and attention might be a consequence of their reduced reading experience combined with weaker musical skills. Comparing DYS+A and DYS-A children suggests that the latter are more resourceful and/or have more effective compensatory strategies, or that their phenotype results from a different developmental trajectory. We will discuss the relevance of these findings for delving into the etiology of these two developmental disorders and address their implications for future research and practice.

Music perception in acquired prosopagnosia

BACKGROUND

Acquired prosopagnosia is often associated with other deficits such as dyschromatopsia and topographagnosia, from damage to adjacent perceptual networks. A recent study showed that some subjects with developmental prosopagnosia also have congenital amusia, but problems with music perception have not been described with the acquired variant.

OBJECTIVE

Our goal was to determine if music perception was also impaired in subjects with acquired prosopagnosia, and if so, its anatomic correlate.

METHOD

We studied eight subjects with acquired prosopagnosia, all of whom had extensive neuropsychological and neuroimaging testing. They performed a battery of tests evaluating pitch and rhythm processing, including the Montréal Battery for the Evaluation of Amusia.

RESULTS

At the group level, subjects with anterior temporal lesions were impaired in pitch perception relative to the control group, but not those with occipitotemporal lesions. Three of eight subjects with acquired prosopagnosia had impaired musical pitch perception while rhythm perception was spared. Two of the three also showed reduced musical memory. These three reported alterations in their emotional experience of music: one reported music anhedonia and aversion, while the remaining two had changes consistent with musicophilia. The lesions of these three subjects affected the right or bilateral temporal poles as well as the right amygdala and insula. None of the three prosopagnosic subjects with lesions limited to the inferior occipitotemporal cortex exhibited impaired pitch perception or musical memory, or reported changes in music appreciation.

CONCLUSION

Together with the results of our previous studies of voice recognition, these findings indicate an anterior ventral syndrome that can include the amnestic variant of prosopagnosia, phonagnosia, and various alterations in music perception, including acquired amusia, reduced musical memory, and subjective reports of altered emotional experience of music.

Human Genomics and the Biocultural Origin of Music

Music is an exclusive feature of humankind. It can be considered as a form of universal communication, only partly comparable to the vocalizations of songbirds. Many trends of research in this field try to address music origins, as well as the genetic bases of musicality. On one hand, several hypotheses have been made on the evolution of music and its role, but there is still debate, and comparative studies suggest a gradual evolution of some abilities underlying musicality in primates. On the other hand, genome-wide studies highlight several genes associated with musical aptitude, confirming a genetic basis for different musical skills which humans show. Moreover, some genes associated with musicality are involved also in singing and song learning in songbirds, suggesting a likely evolutionary convergence between humans and songbirds. This comprehensive review aims at presenting the concept of music as a sociocultural manifestation within the current debate about its biocultural origin and evolutionary function, in the context of the most recent discoveries related to the cross-species genetics of musical production and perception.

Impaired face recognition is associated with abnormal gray matter volume in the posterior cingulate cortex in congenital amusia

Congenital amusia is as a neurodevelopment disorder primarily defined by impairment in pitch discrimination and pitch memory. Interestingly, it has been reported that individuals with congenital amusia also exhibit deficits in face recognition (prosopagnosia). One explanation of such comorbidity is that the neural substrates of pitch recognition and face recognition may be similar. To test this hypothesis, face recognition ability was assessed using the Cambridge Face Memory Test (CFMT) and gray matter volume was determined through voxel-based morphometry (VBM) among participants with and without congenital amusia. As expected, participants with amusia performed worse on the CFMT test and showed reduced gray matter volume (GMV) in the middle temporal gyrus (MTG), the superior temporal gyrus (STG), and the posterior cingulate cortex (PCC) in the right hemisphere, when compared with matched controls. Furthermore, correlation analyses demonstrated that the CFMT score was positively related to MTG, STG, and PCC GMV in all participants, while separate analyses of each group found a positive correlation of CFMT score and PCC GMV in amusics. These findings suggest that face recognition is associated with a widely distributed microstructural network in the human brain and the PCC plays an important role in both pitch recognition and face recognition in amusics. In addition, neurodevelopmental disorders such as congenital amusia and prosopagnosia may share a common neural substrate.

Cortical Morphological Changes in Congenital Amusia: Surface-Based Analyses

Background: Congenital amusia (CA) is a rare disorder characterized by deficits in pitch perception, and many structural and functional magnetic resonance imaging studies have been conducted to better understand its neural bases. However, a structural magnetic resonance imaging analysis using a surface-based morphology method to identify regions with cortical features abnormalities at the vertex-based level has not yet been performed. Methods: Fifteen participants with CA and 13 healthy controls underwent structural magnetic resonance imaging. A surface-based morphology method was used to identify anatomical abnormalities. Then, the surface parameters' mean value of the identified clusters with statistically significant between-group differences were extracted and compared. Finally, Pearson's correlation analysis was used to assess the correlation between the Montreal Battery of Evaluation of Amusia (MBEA) scores and surface parameters. Results: The CA group had significantly lower MBEA scores than the healthy controls (p = 0.000). The CA group exhibited a significant higher fractal dimension in the right caudal middle frontal gyrus and a lower sulcal depth in the right pars triangularis gyrus (p < 0.05; false discovery rate-corrected at the cluster level) compared to healthy controls. There were negative correlations between the mean fractal dimension values in the right caudal middle frontal gyrus and MBEA score, including the mean MBEA score (r = -0.5398, p = 0.0030), scale score (r = -0.5712, p = 0.0015), contour score (r = -0.4662, p = 0.0124), interval score (r = -0.4564, p = 0.0146), rhythmic score (r = -0.5133, p = 0.0052), meter score (r = -0.3937, p = 0.0382), and memory score (r = -0.3879, p = 0.0414). There was a significant positive correlation between the mean sulcal depth in the right pars triangularis gyrus and the MBEA score, including the mean score (r = 0.5130, p = 0.0052), scale score (r = 0.5328, p = 0.0035), interval score (r = 0.4059, p = 0.0321), rhythmic score (r = 0.5733, p = 0.0014), meter score (r = 0.5061, p = 0.0060), and memory score (r = 0.4001, p = 0.0349). Conclusion: Individuals with CA exhibit cortical morphological changes in the right hemisphere. These findings may indicate that the neural basis of speech perception and memory impairments in individuals with CA is associated with abnormalities in the right pars triangularis gyrus and middle frontal gyrus, and that these cortical abnormalities may be a neural marker of CA.

A deep facial recognition system using computational intelligent algorithms

The development of biometric applications, such as facial recognition (FR), has recently become important in smart cities. Many scientists and engineers around the world have focused on establishing increasingly robust and accurate algorithms and methods for these types of systems and their applications in everyday life. FR is developing technology with multiple real-time applications. The goal of this paper is to develop a complete FR system using transfer learning in fog computing and cloud computing. The developed system uses deep convolutional neural networks (DCNN) because of the dominant representation; there are some conditions including occlusions, expressions, illuminations, and pose, which can affect the deep FR performance. DCNN is used to extract relevant facial features. These features allow us to compare faces between them in an efficient way. The system can be trained to recognize a set of people and to learn via an online method, by integrating the new people it processes and improving its predictions on the ones it already has. The proposed recognition method was tested with different three standard machine learning algorithms (Decision Tree (DT), K Nearest Neighbor(KNN), Support Vector Machine (SVM)). The proposed system has been evaluated using three datasets of face images (SDUMLA-HMT, 113, and CASIA) via performance metrics of accuracy, precision, sensitivity, specificity, and time. The experimental results show that the proposed method achieves superiority over other algorithms according to all parameters. The suggested algorithm results in higher accuracy (99.06%), higher precision (99.12%), higher recall (99.07%), and higher specificity (99.10%) than the comparison algorithms.