Dual-echo fMRI can detect activations in inferior temporal lobe during intelligible speech comprehension.

The neural basis of speech comprehension has been investigated intensively during the past few decades. Incoming auditory signals are analysed for speech-like patterns and meaningful information can be extracted by mapping these sounds onto stored semantic representations. Investigation into the neural basis of speech comprehension has largely focused on the temporal lobe, in particular the superior and posterior regions. The ventral anterior temporal lobe (vATL), which includes the inferior temporal gyrus (ITG) and temporal fusiform gyrus (TFG) is consistently omitted in fMRI studies. In contrast, PET studies have shown the involvement of these ventral temporal regions. One crucial factor is the signal loss experienced using conventional echo planar imaging (EPI) for fMRI, at tissue interfaces such as the vATL. One method to overcome this signal loss is to employ a dual-echo EPI technique. The aim of this study was to use intelligible and unintelligible (spectrally rotated) sentences to determine if the vATL could be detected during a passive speech comprehension task using a dual-echo acquisition. A whole brain analysis for an intelligibility contrast showed bilateral superior temporal lobe activations and a cluster of activation within the left vATL. Converging evidence implicates the same ventral temporal regions during semantic processing tasks, which include language processing. The specific role of the ventral temporal region during intelligible speech processing cannot be determined from this data alone, but the converging evidence from PET, MEG, TMS and neuropsychology strongly suggest that it contains the stored semantic representations, which are activated by the speech decoding process.

A comparison of dual gradient-echo and spin-echo fMRI of the inferior temporal lobe.

Magnetic susceptibility differences at tissue interfaces lead to signal loss in conventional gradient-echo (GE) EPI. This poses a problem for fMRI in language and memory paradigms, which activate the most affected regions. Two methods proposed to overcome this are spin-echo EPI and dual GE EPI, where two EPI read-outs are serially collected at a short and longer echo time. The spin-echo method applies a refocusing pulse to recover dephased MR signal due to static field inhomogeneities, but is known to have a relatively low blood oxygenation level dependant (BOLD) sensitivity. In comparison, GE has superior BOLD sensitivity, and by employing an additional shorter echo, in a dual GE sequence, it can reduce signal loss due to spin dephasing. We directly compared dual GE and spin-echo fMRI during a semantic categorization task, which has been shown to activate the inferior temporal region-a region known to be affected by magnetic susceptibility. A whole brain analysis showed that the dual GE resulted in significantly higher activation within the left inferior temporal fusiform (ITF) cortex, compared to spin-echo. The inferior frontal gyrus (IFG) was activated for dual GE, but not spin-echo. Regions of interest analysis was carried out on the anterior and posterior ITF, left and right IFG, and part of the cerebellum. Dual GE outperformed spin-echo in the anterior and posterior ITF and bilateral IFG regions, whilst being equal in the cerebellum. Hence, dual GE should be the method of choice for fMRI studies of inferior temporal regions.

Why bilateral damage is worse than unilateral damage to the brain.

Human and animal lesion studies have shown that behavior can be catastrophically impaired after bilateral lesions but that unilateral damage often produces little or no effect, even controlling for lesion extent. This pattern is found across many different sensory, motor, and memory domains. Despite these findings, there has been no systematic, computational explanation. We found that the same striking difference between unilateral and bilateral damage emerged in a distributed, recurrent attractor neural network. The difference persists in simple feedforward networks, where it can be understood in explicit quantitative terms. In essence, damage both distorts and reduces the magnitude of relevant activity in each hemisphere. Unilateral damage reduces the relative magnitude of the contribution to performance of the damaged side, allowing the intact side to dominate performance. In contrast, balanced bilateral damage distorts representations on both sides, which contribute equally, resulting in degraded performance. The model's ability to account for relevant patient data suggests that mechanisms similar to those in the model may operate in the brain.

The role of plasticity-related functional reorganization in the explanation of central dyslexias.

This investigation explored the hypothesis that patterns of acquired dyslexia may reflect, in part, plasticity-driven relearning that dynamically alters the division of labour (DOL) between the direct, orthography → phonology (O → P) pathway and the semantically mediated, orthography → semantics → phonology (O → S → P) pathway. Three simulations were conducted using a variant of the triangle model of reading. The model demonstrated core characteristics of normal reading behaviour in its undamaged state. When damage was followed by reoptimization (mimicking spontaneous recovery), the model reproduced the deficits observed in the central dyslexias-acute phonological damage combined with recovery matched data taken from a series of 12 phonological dyslexic patients-whilst progressive semantic damage interspersed with recovery reproduced data taken from 100 observations of semantic dementia patients. The severely phonologically damaged model also produced symptoms of deep dyslexia (imageability effects, production of semantic and mixed semantic/visual errors). In all cases, the DOL changed significantly in the recovery period, suggesting that postmorbid functional reorganization is important in understanding behaviour in chronic-stage patients.

Solving the paradox of the equipotential and modular brain: a neurocomputational model of stroke vs. slow-growing glioma.

In acute brain damage (e.g., stroke), patients can be left with specific deficits while other domains are unaffected, consistent with the classical 'modular' view of cortical organization. On this view, relearning of impaired function is limited because the remaining brain regions, tuned to other domains, have minimal capacity to assimilate an alternative activity. A clear paradox arises in low-grade glioma where an even greater amount of cortex may be affected and resected without impairment. Using a neurocomputational model we account for the modular nature of normal function as well as the contrasting types of brain insult through the interaction of three computational principles: patterns of connectivity; experience-dependent plasticity; and the time course of damage. This work provides support for a neo-Lashleyan view of cortical organization.

Using parallel distributed processing models to simulate phonological dyslexia: the key role of plasticity-related recovery.

PMSP96 [Plaut, D. C., McClelland, J. L., Seidenberg, M. S., & Patterson, K. Understanding normal and impaired word reading: Computational principles in quasi-regular domains. Psychological Review, 103, 56-115, 1996, Simulation 4] is an implementation of the triangle model of reading, which was able to simulate effects found in normal and surface dyslexic readers. This study replicated the original findings and explored the possibility that damage to the phonological portion of the model might produce symptoms of phonological dyslexia. The first simulation demonstrated that this implementation of PMSP96 was able to reproduce the standard effects of reading, and that when damaged by removal of the semantic input to phonology, it produced the kind of frequency/consistency interactions and regularization errors typical of surface dyslexia. The second simulation explored the effect of phonological damage. Phonological damage alone did not result in a convincing simulation of phonological dyslexia. However, when the damage was followed by a period of recovery, the network was able to simulate large lexicality and imageability effects characteristic of phonological dyslexia-the first time that both surface and phonological dyslexia have been simulated in the same parallel distributed processing network. This result supports the view that plasticity-related changes should be a significant factor in our understanding of chronic behavioral dissociations.

Exploring the impact of plasticity-related recovery after brain damage in a connectionist model of single-word reading.

The effect of retraining a damaged connectionist model of single-word reading was investigated with the aim of establishing whether plasticity-related changes occurring during the recovery process can contribute to our understanding of the pattern of dissociations found in brain-damaged patients. In particular, we sought to reproduce the strong frequency x consistency interactions found in surface dyslexia. A replication of Plaut, McClelland, Seidenberg, and Patterson's (1996) model of word reading was damaged and then retrained, using a standard backpropagation algorithm. Immediately after damage, there was only a small frequency x consistency interaction. Retraining the damaged model crystallized out these small differences into a strong dissociation, very similar to the pattern found in surface dyslexic patients. What is more, the percentage of regularization errors, always high in surface dyslexics, increased greatly over the retraining period, moving from under 10% to over 80% in some simulations. These results suggest that the performance patterns of brain-damaged patients can owe as much to the substantial changes in the pattern of connectivity occurring during recovery as to the original premorbid structure. This finding is discussed in relation to the traditional cognitive neuropsychological assumptions of subtractivity and transparency.