Mapping the language system: Part 2

This is the second of a multi-part post about a pair of papers that just came out (Mirman et al., 2015, in press). Part 1 was about the behavioral data: we started with 17 behavioral measures from 99 participants with aphasia following left hemisphere stroke. Using factor analysis, we reduced those 17 measures to 4 underlying factors: Semantic Recognition, Speech Production, Speech Recognition, and Semantic Errors. For each of these factors, we then used voxel-based lesion-symptom mapping (VLSM) to identify the left hemisphere regions where stroke damage was associated with poorer performance. 

The speech factors mapped out parallel ventral and dorsal systems around the Sylvian fissure for speech recognition and speech production, respectively.

Credit: Mirman et al., Nature Communications

Speech production deficits were associated with lesions in the "dorsal speech pathway" superior to the Sylvian fissure, primarily in the supramarginal gyrus and extending anteriorly into inferior postcentral, precentral, and premotor cortex (blue-green in the above figure). Speech recognition deficits were associated with lesions in the "ventral speech pathway" inferior to the Sylvian fissure, primarily in the superior temporal gyrus, including Wernicke’s area and extending deep into planum temporale (red-yellow on the above figure). This is somewhat different from the classic Broca-Wernicke-Lichtheim model of language: the speech production system is not localized just to inferior frontal regions ("Broca's area") but extends posteriorly through somatosensory and inferior parietal regions thought to be important for skilled action. In other words, speech production is a skilled action that involves an integrated neural system for motor planning, sensing positions of the articulators, and executing the movements. This is consistent with the frameworks developed by Greg Hickok (e.g., Hickok, 2012; Hickok & Poeppel, 2007) and (independently) Josef Rauschecker (e.g., Rauschecker & Scott, 2009). Our ventral speech recognition stream was largely restricted to the superior temporal gyrus and planum temporale (as in Rauschecker's model; Hickok's model includes middle and inferior temporal regions in speech recognition). Also, we did not find involvement of the auditory system in speech production -- such involvement is a key aspect of Hickok's model, though our orthogonal factors may have contributed to this lack of overlap.

The semantic errors factor was associated with damage to the anterior temporal lobe, which should not be surprising because several previous studies (including previous VLSM with a subset of these participants) have found that left ATL damage is associated with production of semantic errors in picture naming. There is a lot of evidence that the ATLs are neural hubs for a distributed neural system supporting semantic memory. From that perspective, damage to ATL should impair semantic memory and semantic errors are symptom of that impairment. Following that logic, the semantic recognition deficits should also be associated with ATL damage but that's not what we found. Instead, we found that semantic recognition deficits were associated with damage to white matter medial to the insula and lateral to the basal ganglia, where three major tracts converge: the inferior fronto-occipital fasciculus (green in the figure below), the uncinate fasciculus (light blue in the figure below), and the anterior thalamic radiations (dark blue in the figure below).

Credit: Mirman et al., Nature Communications

In the second paper of the pair (in press at Neuropsychologia) we used a multivariate lesion-symptom mapping approach based on support-vector regression (Zhang et al., 2014) to re-analyze these data and ruled out some methodological VLSM issues as possible causes of this result. That paper discusses the implications of these results in more detail, but the upshot is that each of these tracts is important for semantic memory because they connect the frontal lobe with the distributed neural system involved in semantic memory. Our finding suggests that the convergence of these tracts creates a vulnerable "white matter bottleneck" where a small amount of damage can have a big effect on the connections between the frontal lobe and the rest of the brain.

Hickok G (2012). Computational neuroanatomy of speech production. Nature Reviews Neuroscience, 13 (2), 135-145. PMID: 22218206
Hickok, G. S., & Poeppel, D. (2007). The cortical organization of speech processing Nature Reviews Neuroscience, 8 (May), 393-402.
Mirman, D., Chen, Q., Zhang, Y., Wang, Z., Faseyitan, O.K., Coslett, H.B., & Schwartz, M.F. (2015a). Neural Organization of Spoken Language Revealed by Lesion-Symptom Mapping. Nature Communications, 6 (6762), 1-9. DOI: 10.1038/ncomms7762.
Mirman, D., Zhang, Y., Wang, Z., Coslett, H.B., & Schwartz, M.F. (in press). The ins and outs of meaning: Behavioral and neuroanatomical dissociation of semantically-driven word retrieval and multimodal semantic recognition in aphasia. Neuropsychologia. DOI: 10.1016/j.neuropsychologia.2015.02.014.
Rauschecker J.P., & Scott S.K. (2009). Maps and streams in the auditory cortex: nonhuman primates illuminate human speech processing. Nature Neuroscience, 12 (6), 718-724 PMID: 19471271
Zhang Y., Kimberg D.Y., Coslett H.B., Schwartz M.F., & Wang Z. (2014). Multivariate lesion-symptom mapping using support vector regression. Human Brain Mapping, 35 (12), 5861-5876. PMID: 25044213