Functional asymmetry and effective connectivity of the auditory system during speech perception is modulated by the place of articulation of the consonant- A 7T fMRI study

The emergence of machine learning in auditory neural impairment: A systematic review

Hearing loss is a common neurodegenerative disease that can start at any stage of life. Misalignment of the auditory neural impairment may impose challenges in processing incoming auditory stimulus that can be measured using electroencephalography (EEG). The electrophysiological behaviour response emanated from EEG auditory evoked potential (AEP) requires highly trained professionals for analysis and interpretation. Reliable automated methods using techniques of machine learning would assist the auditory assessment process for informed treatment and practice. It is thus highly required to develop models that are more efficient and precise by considering the characteristics of brain signals. This study aims to provide a comprehensive review of several state-of-the-art techniques of machine learning that adopt EEG evoked response for the auditory assessment within the last 13 years. Out of 161 initially screened articles, 11 were retained for synthesis. The outcome of the review presented that the Support Vector Machine (SVM) classifier outperformed with over 80% accuracy metric and was recognized as the best suited model within the field of auditory research. This paper discussed the comprehensive iterative properties of the proposed computed algorithms and the feasible future direction in hearing impaired rehabilitation.

Acoustics versus linguistics? Context is Part and Parcel to lateralized processing of the parts and parcels of speech

The purpose of this review is to provide an accessible exploration of key considerations of lateralization in speech and non-speech perception using clear and defined language. From these considerations, the primary arguments for each side of the linguistics versus acoustics debate are outlined and explored in context of emerging integrative theories. This theoretical approach entails a perspective that linguistic and acoustic features differentially contribute to leftward bias, depending on the given context. Such contextual factors include stimulus parameters and variables of stimulus presentation (e.g., noise/silence and monaural/binaural) and variances in individuals (sex, handedness, age, and behavioural ability). Discussion of these factors and their interaction is also aimed towards providing an outline of variables that require consideration when developing and reviewing methodology of acoustic and linguistic processing laterality studies. Thus, there are three primary aims in the present paper: (1) to provide the reader with key theoretical perspectives from the acoustics/linguistics debate and a synthesis of the two viewpoints, (2) to highlight key caveats for generalizing findings regarding predominant models of speech laterality, and (3) to provide a practical guide for methodological control using predominant behavioural measures (i.e., gap detection and dichotic listening tasks) and/or neurophysiological measures (i.e., mismatch negativity) of speech laterality.

Interhemispheric interactions during sentence comprehension in patients with aphasia

Right-hemisphere involvement in language processing following left-hemisphere damage may reflect either compensatory processes, or a release from homotopic transcallosal inhibition, resulting in excessive right-to-left suppression that is maladaptive for language performance. Using fMRI, we assessed inter-hemispheric effective connectivity in fifteen patients with post-stroke aphasia, along with age-matched and younger controls during a sentence comprehension task. Dynamic Causal Modeling was used with four bilateral regions including inferior frontal gyri (IFG) and primary auditory cortices (A1). Despite the presence of lesions, satisfactory model fit was obtained in 9/15 patients. In young controls, the only significant homotopic connection (RA1-LA1), was excitatory, while inhibitory connections emanated from LIFG to both left and right A1's. Interestingly, these connections were also correlated with language comprehension scores in patients. The results for homotopic connections show that excitatory connectivity from RA1-to-LA1 and inhibitory connectivity from LA1-to-RA1 are associated with general auditory verbal comprehension. Moreover, negative correlations were found between sentence comprehension and top-down coupling for both heterotopic (LIFG-to-RA1) and intra-hemispheric (LIFG-to-LA1) connections. These results do not show an emergence of a new compensatory right to left excitation in patients nor do they support the existence of left to right transcallosal suppression in controls. Nevertheless, the correlations with performance in patients are consistent with some aspects of both the compensation model, and the transcallosal suppression account for the role of the RH. Altogether our results suggest that changes to both excitatory and inhibitory homotopic and heterotopic connections due to LH damage may be maladaptive, as they disrupt the normal inter-hemispheric coordination and communication.

Vowels and Consonants in the Brain: Evidence from Magnetoencephalographic Studies on the N1m in Normal-Hearing Listeners

Speech sound perception is one of the most fascinating tasks performed by the human brain. It involves a mapping from continuous acoustic waveforms onto the discrete phonological units computed to store words in the mental lexicon. In this article, we review the magnetoencephalographic studies that have explored the timing and morphology of the N1m component to investigate how vowels and consonants are computed and represented within the auditory cortex. The neurons that are involved in the N1m act to construct a sensory memory of the stimulus due to spatially and temporally distributed activation patterns within the auditory cortex. Indeed, localization of auditory fields maps in animals and humans suggested two levels of sound coding, a tonotopy dimension for spectral properties and a tonochrony dimension for temporal properties of sounds. When the stimulus is a complex speech sound, tonotopy and tonochrony data may give important information to assess whether the speech sound parsing and decoding are generated by pure bottom-up reflection of acoustic differences or whether they are additionally affected by top-down processes related to phonological categories. Hints supporting pure bottom-up processing coexist with hints supporting top-down abstract phoneme representation. Actually, N1m data (amplitude, latency, source generators, and hemispheric distribution) are limited and do not help to disentangle the issue. The nature of these limitations is discussed. Moreover, neurophysiological studies on animals and neuroimaging studies on humans have been taken into consideration. We compare also the N1m findings with the investigation of the magnetic mismatch negativity (MMNm) component and with the analogous electrical components, the N1 and the MMN. We conclude that N1 seems more sensitive to capture lateralization and hierarchical processes than N1m, although the data are very preliminary. Finally, we suggest that MEG data should be integrated with EEG data in the light of the neural oscillations framework and we propose some concerns that should be addressed by future investigations if we want to closely line up language research with issues at the core of the functional brain mechanisms.