Recruitment of Language-, Emotion- and Speech-Timing Associated Brain Regions for Expressing Emotional Prosody: Investigation of Functional Neuroanatomy with fMRI

We aimed to progress understanding of prosodic emotion expression by establishing brain regions active when expressing specific emotions, those activated irrespective of the target emotion, and those whose activation intensity varied depending on individual performance. BOLD contrast data were acquired whilst participants spoke non-sense words in happy, angry or neutral tones, or performed jaw-movements. Emotion-specific analyses demonstrated that when expressing angry prosody, activated brain regions included the inferior frontal and superior temporal gyri, the insula, and the basal ganglia. When expressing happy prosody, the activated brain regions also included the superior temporal gyrus, insula, and basal ganglia, with additional activation in the anterior cingulate. Conjunction analysis confirmed that the superior temporal gyrus and basal ganglia were activated regardless of the specific emotion concerned. Nevertheless, disjunctive comparisons between the expression of angry and happy prosody established that anterior cingulate activity was significantly higher for angry prosody than for happy prosody production. Degree of inferior frontal gyrus activity correlated with the ability to express the target emotion through prosody. We conclude that expressing prosodic emotions (vs. neutral intonation) requires generic brain regions involved in comprehending numerous aspects of language, emotion-related processes such as experiencing emotions, and in the time-critical integration of speech information

Network-Level Structural Abnormalities of Cerebral Cortex in Type 1 Diabetes Mellitus

Type 1 diabetes mellitus (T1DM) usually begins in childhood and adolescence and causes lifelong damage to several major organs including the brain. Despite increasing evidence of T1DM-induced structural deficits in cortical regions implicated in higher cognitive and emotional functions, little is known whether and how the structural connectivity between these regions is altered in the T1DM brain. Using inter-regional covariance of cortical thickness measurements from high-resolution T1-weighted magnetic resonance data, we examined the topological organizations of cortical structural networks in 81 T1DM patients and 38 healthy subjects. We found a relative absence of hierarchically high-level hubs in the prefrontal lobe of T1DM patients, which suggests ineffective top-down control of the prefrontal cortex in T1DM. Furthermore, inter-network connections between the strategic/executive control system and systems subserving other cortical functions including language and mnemonic/emotional processing were also less integrated in T1DM patients than in healthy individuals. The current results provide structural evidence for T1DM-related dysfunctional cortical organization, which specifically underlie the top-down cognitive control of language, memory, and emotion. © 2013 Lyoo et al

Brain Asymmetry in Evolution

In higher mammals, including primates and carnivores, the asymmetrical aspects of brain morphology and function have been shown to be species-related, sex-related, and subject to individual diversity, and are associated with cognition, emotion, language, preference of hand/paw use, and numerous other aspects. Disturbance of the brain lateralization is involved in human neurodevelopmental disorders with cognitive impairments, social deficits, and/or specific language impairments. Asymmetric development may be essential to the evolution of the brain in acquiring higher and/or more diverse functions. The purpose of this Special Issue on “Brain Asymmetry in Evolution” is to highlight morphological and functional lateralization of the brain in various species of mammals toward understanding the evolution of the brain

Lost for emotion words: what motor and limbic brain activity reveals about autism and semantic theory.

Autism spectrum conditions (ASC) are characterised by deficits in understanding and expressing emotions and are frequently accompanied by alexithymia, a difficulty in understanding and expressing emotion words. Words are differentially represented in the brain according to their semantic category and these difficulties in ASC predict reduced activation to emotion-related words in limbic structures crucial for affective processing. Semantic theories view 'emotion actions' as critical for learning the semantic relationship between a word and the emotion it describes, such that emotion words typically activate the cortical motor systems involved in expressing emotion actions such as facial expressions. As ASC are also characterised by motor deficits and atypical brain structure and function in these regions, motor structures would also be expected to show reduced activation during emotion-semantic processing. Here we used event-related fMRI to compare passive processing of emotion words in comparison to abstract verbs and animal names in typically-developing controls and individuals with ASC. Relatively reduced brain activation in ASC for emotion words, but not matched control words, was found in motor areas and cingulate cortex specifically. The degree of activation evoked by emotion words in the motor system was also associated with the extent of autistic traits as revealed by the Autism Spectrum Quotient. We suggest that hypoactivation of motor and limbic regions for emotion word processing may underlie difficulties in processing emotional language in ASC. The role that sensorimotor systems and their connections might play in the affective and social-communication difficulties in ASC is discussed.This work was supported by the Medical Research Council (MRC) (MC_US_A060_0034, U1055.04.003.00001.01 to F.P., MC_US_A060_0043, MC-A060-5PQ90 to Y. S., MRC studentship to R.M.).The is the final published paper originally published in NeuroImage under a CC-BY licence (RL Moseley, Y Shtyrov, B Mohr, MV Lombardo, S Baron-Cohen, F Pulvermüller, NeuroImage 2015, 104, 413-422

Methods and Approaches for Characterizing Learning Related Changes Observed in functional MRI Data — A Review

Brain imaging data have so far revealed a wealth of information about neuronal circuits involved in higher mental functions like memory, attention, emotion, language etc. Our efforts are toward understanding the learning related effects in brain activity during the acquisition of visuo-motor sequential skills. The aim of this paper is to survey various methods and approaches of analysis that allow the characterization of learning related changes in fMRI data. Traditional imaging analysis using the Statistical Parametric Map (SPM) approach averages out temporal changes and presents overall differences between different stages of learning. We outline other potential approaches for revealing learning effects such as statistical time series analysis, modelling of haemodynamic response function and independent component analysis. We present example case studies from our visuo-motor sequence learning experiments to describe application of SPM and statistical time series analyses. Our review highlights that the problem of characterizing learning induced changes in fMRI data remains an interesting and challenging open research problem

Abnormal Changes of Brain Cortical Anatomy and the Association with Plasma MicroRNA107 Level in Amnestic Mild Cognitive Impairment

MicroRNA107 (Mir107) has been thought to relate to the brain structure phenotype of Alzheimer’s disease. In this study, we evaluated the cortical anatomy in amnestic mild cognitive impairment (aMCI) and the relation between cortical anatomy and plasma levels of Mir107 and beta-site amyloid precursor protein (APP) cleaving enzyme 1 (BACE1). Twenty aMCI (20 aMCI) and 24 cognitively normal control (NC) subjects were recruited, and T1-weighted MR images were acquired. Cortical anatomical measurements, including cortical thickness (CT), surface area (SA), and local gyrification index (LGI), were assessed. Quantitative RT-PCR was used to examine plasma expression of Mir107, BACE1 mRNA. Thinner cortex was found in aMCI in areas associated with episodic memory and language, but with thicker cortex in other areas. SA decreased in aMCI in the areas associated with working memory and emotion. LGI showed a significant reduction in aMCI in the areas involved in language function. Changes in Mir107 and BACE1 messenger RNA plasma expression were correlated with changes in CT and SA. We found alterations in key left brain regions associated with memory, language, and emotion in aMCI that were significantly correlated with plasma expression of Mir107 and BACE1 mRNA. This combination study of brain anatomical alterations and gene information may shed lights on our understanding of the pathology of AD

The Body, Its Emotions, the Self, and Consciousness

This article proposes a means for better understanding the self and consciousness. Data indicate that the basic “emotional brain” continually computes potential survival risk against reward to rank consequent “emotion scores” for all sensory inputs. These scores compete to yield winner-takes-all outcomes that determine the choice of attention or action. This mechanism prevails regardless of whether the competing options gain their emotion scores through a rational or an intuitive pathway. There is no need to postulate any homunculus or inner self in control of such choice; indeed, our belief in a first-person self in overall control is wrong.The self is a passive construct arising from each individual’s social development, where language acquisition vastly heightens communication and awareness not only outwardly, but also inwardly, as if to a controlling “inner I.” However, when society comes to hold the maturing being accountable for his or her actions, the brain must respond, and it does so in the only way it can, by deeming that this passive, inner self-construct act as if it were the active self in charge. Consciousness emerges when the language-based output of the higher brain is referred for ownership to this artificial self-construct

Analyzing brain activity in understanding cultural and language interaction for depression and anxiety

Human brain has always been considered as a black box and is the source of all emotions. Analyzing cultural and language role through human emotion by looking at the brain activity can thus help us understand depression and stress better. This paper focuses on understanding and analyzing undergraduate students’ emotions with different background and culture after completing their semester final examination. Brain wave signals were captured using EEG device and analyzed through proposing an affective computation model. EEG signal was collected from 8 healthy subjects from different states of Malaysia with different dialects where each subject was emotionally induced with audio and video emotion stimuli using the International Affective Pictures and System (IAPS). Features were extracted from the captured EEG signals using Kernel Density Estimation (KDE), which was then categorized into four basic emotions of happy, calm, sad and fear using the Multi-layer Perceptron (MLP). Results of the study show potential of using such analysis in understanding stress, anxiety and depression