Approaches to the cortical analysis of auditory objects

Griffiths, Timothy D.; Kumar, Sukhbinder; Warren, Jason D.; Stewart, Lauren; Stephan, Klaas Ε.; Friston, Karl J.

doi:10.1016/j.heares.2007.01.010

Cited by 28 publications

(23 citation statements)

References 27 publications

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“…Recent work by Griffiths et al (2007) and Kumar et al (2007) applied dynamic causal modeling to investigate the effective connectivity within the temporal cortex during spectral envelope analysis of synthesized auditory stimuli. In these studies, a serial processing stream between HG and PT and between PT and STS was detected.…”

Section: Discussionmentioning

confidence: 99%

“…In these studies, a serial processing stream between HG and PT and between PT and STS was detected. Griffiths et al (2007) suggested that the same serial processing stream, HG-PT-STS, could explain deficits in auditory processing observed in a patient suffering from dystimbria. In our study, the serial streams between PT and STS and between planum polare and STS were not observed in the current GCM analysis, nor was GCM analysis performed where planum temporale or polare was used as a reference VOI during GCM analysis.…”

Section: Discussionmentioning

confidence: 99%

“…In our study, the serial streams between PT and STS and between planum polare and STS were not observed in the current GCM analysis, nor was GCM analysis performed where planum temporale or polare was used as a reference VOI during GCM analysis. The latter analysis may have yielded serial circuitry described by Griffiths et al (2007) (i.e., PT to STS). These contrasting findings may be related to differences in the types of auditory stimuli presented.…”

Section: Discussionmentioning

confidence: 99%

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Effective and Structural Connectivity in the Human Auditory Cortex

Upadhyay¹,

Silver²,

Knaus³

et al. 2008

J. Neurosci.

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Language processing involves multiple neuronal structures in the human auditory cortex. Although a variety of neuroimaging and mapping techniques have been implemented to better understand language processing at the level of the auditory cortex, much is unknown regarding how and by what pathways these structures interact during essential tasks such as sentence comprehension. In this study, the effective and structural connectivity at the level of the auditory cortex were investigated. First, blood oxygenation leveldependent (BOLD) responses were measured with time-resolved functional magnetic resonance imaging (fMRI) during audition of short sentences. Once BOLD activation maps were obtained, the effective connectivity between primary auditory cortex and the surrounding auditory regions on the supratemporal plane and superior temporal gyrus (STG) were investigated using Granger causality mapping (GCM). Effective connectivity was observed between the primary auditory cortex and (1) the lateral planum polare and anterior STG, and (2) the lateral planum temporale and posterior STG. By using diffusion tensor probabilistic mapping (DTPM), rostral and caudal fiber pathways were detected between regions depicting effective connectivity. The effective and structural connectivity results of the present study provide further insight as to how auditory stimuli (i.e., human language) is processed at the level of the auditory cortex. Furthermore, combining BOLD fMRI-based GCM and DTPM analysis could provide a novel means to study effective and structural connectivity not only in the auditory cortex, but also in other cortical regions.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Effective and Structural Connectivity in the Human Auditory Cortex

Upadhyay¹,

Silver²,

Knaus³

et al. 2008

J. Neurosci.

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“…11 Some tone-deaf subjects, however, describe music as unpleasant and try to avoid it: similar behaviour has been observed in patients with stroke who developed deficits in the analysis of pitch-sequences and timbre ('dystimbria'). 12 It will be of considerable interest to assess timbre analysis in congenital forms of musical agnosia.…”

Section: Characterising a Complex Phenotypementioning

confidence: 99%

Tone deafness: a model complex cortical phenotype

Griffiths

2008

Clinical Medicine

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-We all know people with tone deafness: these are the people who get thrown out of the choir at school. Although tone deafness is recognised as an output disorder, recent studies have characterised it as one of music perception in the absence of deafness or any associated cognitive disorder. The disorder can therefore be characterised as a form of auditory agnosia. This article considers how the phenotype might be deconstructed to the level of a causal deficit in the perception of pitch pattern. Based on our evolving understanding of the normal brain bases for this process a cortical deficit beyond primary cortex would be predicted. In tone deafness, structural cortical variations have been demonstrated by recent studies that detect subtle changes in the cortical mantle and underlying white matter: these changes are within a right hemisphere network for pitch pattern analysis and working memory for pitch. Studies of multiply affected families are underway to see if the disruption of this network can be caused by single genes. This disorder therefore offers the opportunity to study how a complex phenotype can be characterised as a cortical perceptual disorder potentially explained by a single gene or molecule. Although tone deafness is not pernicious, the underlying abnormality may prove to be a disorder of cortical connectivity that provides a model for disorders that are more so, such as schizophrenia.

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“…The neuronal dynamics are described by the differential equations describing the dynamics of a single state that summarizes the neuronal or synaptic activity of each area; this activity then induces a hemodynamic response as described by an extended Balloon model (Buxton et al, 1998). Examples of DCM for fMRI can be found in Mechelli et al (2004), Noppeney et al (2006), Stephan et al (2005), and Griffiths et al (2007) (for a review on the conceptual basis of DCM and its implementation for functional magnetic resonance imaging data and event-related potentials, see Stephan et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Dynamic causal modelling for fMRI: A two-state model

2008

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Dynamical causal modelling (DCM) for functional magnetic resonance imaging (fMRI) is a technique to infer directed connectivity among brain regions. These models distinguish between a neuronal level, which models neuronal interactions among regions, and an observation level, which models the hemodynamic responses each region. The original DCM formulation considered only one neuronal state per region. In this work, we adopt a more plausible and less constrained neuronal model, using two neuronal states (populations) per region. Critically, this gives us an explicit model of intrinsic (between-population) connectivity within a region. In addition, by using positivity constraints, the model conforms to the organization of real cortical hierarchies, whose extrinsic connections are excitatory (glutamatergic). By incorporating two populations within each region we can model selective changes in both extrinsic and intrinsic connectivity.Using synthetic data, we show that the two-state model is internal consistent and identifiable. We then apply the model to real data, explicitly modelling intrinsic connections. Using model comparison, we found that the two-state model is better than the single-state model. Furthermore, using the two-state model we find that it is possible to disambiguate between subtle changes in coupling; we were able to show that attentional gain, in the context of visual motion processing, is accounted for sufficiently by an increased sensitivity of excitatory populations of neurons in V5, to forward afferents from earlier visual areas.

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Approaches to the cortical analysis of auditory objects

Cited by 28 publications

References 27 publications

Effective and Structural Connectivity in the Human Auditory Cortex

Effective and Structural Connectivity in the Human Auditory Cortex

Tone deafness: a model complex cortical phenotype

Dynamic causal modelling for fMRI: A two-state model

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