Perceptual learning of tone patterns changes the effective connectivity between Heschl's gyrus and planum temporale

Network dynamics underlying alterations in apparent object size

A target circle surrounded by small circles looks larger than an identical circle surrounded by large circles (termed as the Ebbinghaus illusion). While previous research has shown that both early and high-level visual regions are involved in the generation of the illusion, it remains unclear how these regions work together to modulate the illusion effect. Here, we used functional MRI and dynamic causal modelling to investigate the neural networks underlying the illusion in conditions where the focus of attention was manipulated via participants directing their attention to and maintain fixation on only one of the two illusory configurations at a time. Behavioural findings confirmed the presence of the illusion. Accordingly, functional MRI activity in the extrastriate cortex accounted for the illusory effects: apparently larger circles elicited greater activation than apparently smaller circles. Interestingly, this spread of activity for size overestimation was accompanied by a decrease in the inhibitory self-connection in the extrastriate region, and an increase in the feedback connectivity from the precuneus to the extrastriate region. These findings demonstrate that the representation of apparent object size relies on feedback projections from higher- to lower-level visual areas, highlighting the crucial role of top-down signals in conscious visual perception.

Abnormal resting-state effective connectivity in large-scale networks among obsessive-compulsive disorder

BACKGROUND

Obsessive-compulsive disorder (OCD) is a chronic mental illness characterized by abnormal functional connectivity among distributed brain regions. Previous studies have primarily focused on undirected functional connectivity and rarely reported from network perspective.

METHODS

To better understand between or within-network connectivities of OCD, effective connectivity (EC) of a large-scale network is assessed by spectral dynamic causal modeling with eight key regions of interests from default mode (DMN), salience (SN), frontoparietal (FPN) and cerebellum networks, based on large sample size including 100 OCD patients and 120 healthy controls (HCs). Parametric empirical Bayes (PEB) framework was used to identify the difference between the two groups. We further analyzed the relationship between connections and Yale-Brown Obsessive Compulsive Scale (Y-BOCS).

RESULTS

OCD and HCs shared some similarities of inter- and intra-network patterns in the resting state. Relative to HCs, patients showed increased ECs from left anterior insula (LAI) to medial prefrontal cortex, right anterior insula (RAI) to left dorsolateral prefrontal cortex (L-DLPFC), right dorsolateral prefrontal cortex (R-DLPFC) to cerebellum anterior lobe (CA), CA to posterior cingulate cortex (PCC) and to anterior cingulate cortex (ACC). Moreover, weaker from LAI to L-DLPFC, RAI to ACC, and the self-connection of R-DLPFC. Connections from ACC to CA and from L-DLPFC to PCC were positively correlated with compulsion and obsession scores (r = 0.209, p = 0.037; r = 0.199, p = 0.047, uncorrected).

CONCLUSIONS

Our study revealed dysregulation among DMN, SN, FPN, and cerebellum in OCD, emphasizing the role of these four networks in achieving top-down control for goal-directed behavior. There existed a top-down disruption among these networks, constituting the pathophysiological and clinical basis.

High-fidelity transmission of auditory symbolic material is associated with reduced right-left neuroanatomical asymmetry between primary auditory regions

The intergenerational stability of auditory symbolic systems, such as music, is thought to rely on brain processes that allow the faithful transmission of complex sounds. Little is known about the functional and structural aspects of the human brain which support this ability, with a few studies pointing to the bilateral organization of auditory networks as a putative neural substrate. Here, we further tested this hypothesis by examining the role of left-right neuroanatomical asymmetries between auditory cortices. We collected neuroanatomical images from a large sample of participants (nonmusicians) and analyzed them with Freesurfer's surface-based morphometry method. Weeks after scanning, the same individuals participated in a laboratory experiment that simulated music transmission: the signaling games. We found that high accuracy in the intergenerational transmission of an artificial tone system was associated with reduced rightward asymmetry of cortical thickness in Heschl's sulcus. Our study suggests that the high-fidelity copying of melodic material may rely on the extent to which computational neuronal resources are distributed across hemispheres. Our data further support the role of interhemispheric brain organization in the cultural transmission and evolution of auditory symbolic systems.

Preterm neonates distinguish rhythm violation through a hierarchy of cortical processing

Rhythm is a fundamental component of the auditory world, present even during the prenatal life. While there is evidence that some auditory capacities are already present before birth, whether and how the premature neural networks process auditory rhythm is yet not known. We investigated the neural response of premature neonates at 30-34 weeks gestational age to violations from rhythmic regularities in an auditory sequence using high-resolution electroencephalography and event-related potentials. Unpredicted rhythm violations elicited a fronto-central mismatch response, indicating that the premature neonates detected the rhythmic regularities. Next, we examined the cortical effective connectivity underlying the elicited mismatch response using dynamic causal modeling. We examined the connectivity between cortical sources using a set of 16 generative models that embedded alternate hypotheses about the role of the frontal cortex as well as backward fronto-temporal connection. Our results demonstrated that the processing of rhythm violations was not limited to the primary auditory areas, and as in the case of adults, encompassed a hierarchy of temporo-frontal cortical structures. The result also emphasized the importance of top-down (backward) projections from the frontal cortex in explaining the mismatch response. Our findings demonstrate a sophisticated cortical structure underlying predictive rhythm processing at the onset of the thalamocortical and cortico-cortical circuits, two months before term.

From descriptive connectome to mechanistic connectome: Generative modeling in functional magnetic resonance imaging analysis

As a newly emerging field, connectomics has greatly advanced our understanding of the wiring diagram and organizational features of the human brain. Generative modeling-based connectome analysis, in particular, plays a vital role in deciphering the neural mechanisms of cognitive functions in health and dysfunction in diseases. Here we review the foundation and development of major generative modeling approaches for functional magnetic resonance imaging (fMRI) and survey their applications to cognitive or clinical neuroscience problems. We argue that conventional structural and functional connectivity (FC) analysis alone is not sufficient to reveal the complex circuit interactions underlying observed neuroimaging data and should be supplemented with generative modeling-based effective connectivity and simulation, a fruitful practice that we term "mechanistic connectome." The transformation from descriptive connectome to mechanistic connectome will open up promising avenues to gain mechanistic insights into the delicate operating principles of the human brain and their potential impairments in diseases, which facilitates the development of effective personalized treatments to curb neurological and psychiatric disorders.

Music in the brain

Music is ubiquitous across human cultures - as a source of affective and pleasurable experience, moving us both physically and emotionally - and learning to play music shapes both brain structure and brain function. Music processing in the brain - namely, the perception of melody, harmony and rhythm - has traditionally been studied as an auditory phenomenon using passive listening paradigms. However, when listening to music, we actively generate predictions about what is likely to happen next. This enactive aspect has led to a more comprehensive understanding of music processing involving brain structures implicated in action, emotion and learning. Here we review the cognitive neuroscience literature of music perception. We show that music perception, action, emotion and learning all rest on the human brain's fundamental capacity for prediction - as formulated by the predictive coding of music model. This Review elucidates how this formulation of music perception and expertise in individuals can be extended to account for the dynamics and underlying brain mechanisms of collective music making. This in turn has important implications for human creativity as evinced by music improvisation. These recent advances shed new light on what makes music meaningful from a neuroscientific perspective.

Musicianship and melodic predictability enhance neural gain in auditory cortex during pitch deviance detection

When listening to music, pitch deviations are more salient and elicit stronger prediction error responses when the melodic context is predictable and when the listener is a musician. Yet, the neuronal dynamics and changes in connectivity underlying such effects remain unclear. Here, we employed dynamic causal modeling (DCM) to investigate whether the magnetic mismatch negativity response (MMNm)-and its modulation by context predictability and musical expertise-are associated with enhanced neural gain of auditory areas, as a plausible mechanism for encoding precision-weighted prediction errors. Using Bayesian model comparison, we asked whether models with intrinsic connections within primary auditory cortex (A1) and superior temporal gyrus (STG)-typically related to gain control-or extrinsic connections between A1 and STG-typically related to propagation of prediction and error signals-better explained magnetoencephalography responses. We found that, compared to regular sounds, out-of-tune pitch deviations were associated with lower intrinsic (inhibitory) connectivity in A1 and STG, and lower backward (inhibitory) connectivity from STG to A1, consistent with disinhibition and enhanced neural gain in these auditory areas. More predictable melodies were associated with disinhibition in right A1, while musicianship was associated with disinhibition in left A1 and reduced connectivity from STG to left A1. These results indicate that musicianship and melodic predictability, as well as pitch deviations themselves, enhance neural gain in auditory cortex during deviance detection. Our findings are consistent with predictive processing theories suggesting that precise and informative error signals are selected by the brain for subsequent hierarchical processing.