Abstract
In the dual-stream model of language processing, the exact connectivity of the ventral stream to the anterior temporal lobe remains elusive. To investigate the connectivity among the inferior frontal gyrus (IFG) and the lateral part of the temporal and parietal lobes, we integrated spatiotemporal profiles of cortico-cortical evoked potentials (CCEPs) recorded intraoperatively from 14 patients who had had resective surgeries for brain tumor or epileptic focus. The 4D visualization of the combined CCEP data showed that the pars opercularis (Broca’s area) connected to the posterior temporal cortices and the supramarginal gyrus, while the pars orbitalis connected to the anterior lateral temporal cortices and the angular gyrus. Quantitative topographical analysis of CCEP connectivity confirmed an anterior-posterior gradient of connectivity from IFG stimulus sites to the temporal response sites. Reciprocality analysis indicated that the anterior part of the IFG is bi-directionally connected to the temporal or parietal area. The present study revealed that each IFG subdivision has a different connectivity to the temporal lobe with an anterior-posterior gradient and supports the classical connectivity concept of Dejerine that the frontal lobe is connected to the temporal lobe through the arcuate fasciculus and also a double-fan-shaped structure, anchored at the limen insulae.
Language is a unique feature of human beings that should not be impaired by surgery without the justification of clinical benefit. The posterior part of the inferior frontal gyrus (IFG), which consists of the pars opercularis (pOpe) and the pars triangularis (pTri), is known as Broca’s area, while the anterior part, the pars orbitalis (pOrb), is reported to have an executive function in semantic cognition tasks (Wagner AD et al. 2001; Gough PM et al. 2005; Hoffman P et al. 2010; Krieger-Redwood K et al. 2015). Recently, a dual-stream model of language processing has been proposed and has received wide recognition on the strength of an analogy with the processing of visual information (Hickok G and D Poeppel 2004, 2007; Saur D et al. 2008; Ueno T et al. 2011; Hickok G 2012; Gil-Robles S et al. 2013). The model consists of a dorsal stream for phonological processing and a ventral stream for semantic processing. Although this framework is generally accepted, the details of the tracts and cortices involved in the dual network remain to be established (Dick AS and P Tremblay 2012). While the superior longitudinal fasciculus (SLF) and the arcuate fasciculus (AF) are established as the main pathway of the dorsal network, additional studies are required to identify the connectivity underlying the ventral network, which presumably includes the uncinate fasciculus (UF), the inferior longitudinal fasciculus (ILF), and the inferior fronto-occipital fasciculus (IFOF).
Among these, the IFOF is reported to be involved in semantic processing based on high-frequency electrical stimulation of the white matter in awake surgery (Duffau H et al. 2005). The IFOF consists of two components, superficial and deep. The former originates from the anterior part of IFG (pOrb and pTri), while the latter originates from the dorsolateral prefrontal cortex, the middle frontal gyrus, and the orbitofrontal cortex (Sarubbo S et al. 2013). Their posterior termination includes the occipital lobe, the superior parietal lobule, and the posterior part of temporo-basal area (Martino J, C Brogna, et al. 2010). Duffau and coworkers reported that stimulation of the superficial component of the IFOF induced semantic errors during picture naming. The supposition that IFOF engages in semantic processing is also supported by functional studies on its cortical terminations. The anterior part of the IFG, which is part of the frontal termination of the superficial component of IFOF, has been shown to be engaged in semantic control by meta-analysis of functional magnetic resonance imaging (fMRI) and positron-emission tomographic (PET) studies (Noonan KA et al. 2013) and by interventions using transcranial magnetic stimulation (TMS) (Hoffman P et al. 2010; Jefferies E 2013). The posterior fusiform gyrus, one of the posterior terminations of IFOF, is known as the visual word-form area. A role for IFOF in semantic processing is further supported by dynamic causality modeling of BOLD (blood oxygenation level dependent) signals that showed effective connectivity from the fusiform gyrus to the anterior IFG during a semantic judgment task (Perrone-Bertolotti M et al. 2017). These pieces of evidence suggest that the superficial component of the IFOF has a semantic function. However, the anterior temporal lobe (ATL), which engages in semantic representation and is essential in semantic cognition (Spitsyna G et al. 2006; Lambon Ralph MA et al. 2010; Jefferies E 2013; Lambon Ralph MA et al. 2017), has not been reported as a posterior termination of the IFOF. ATL subregions receive the termination of the UF (temporal pole) and ILF (anterior-ventral area and temporal pole) (Binney RJ et al. 2012; Fan L et al. 2014; Egger K et al. 2015; Jung J et al. 2017; Panesar SS et al. 2018), although they seem not to be a main part of the ventral spoken language stream. Electrical stimulation of the UF does not interfere with object naming and resection of the UF is generally acceptable in neurosurgery (Duffau H et al. 2008; Duffau H et al. 2009). The ILF projects posteriorly to the occipital lobe without any frontal termination. If the superficial component of the IFOF and the anterior part of the IFG are implicated in semantic function, it would be natural to infer that the anterior temporal lobe, which is the semantic representational hub, has a direct connection to the semantic control center (the anterior part of IFG) via a subcomponent of the IFOF, although no termination of the IFOF in the anterior temporal lobe has been proven. To verify this hypothesis, we investigated in detail the connectivity between the IFG and the lateral temporal cortices.
The cortico-cortical evoked potential (CCEP) is an electrophysiological method to probe effective connectivity by applying single-pulse electrical stimulation to the cortex. The CCEPs are recorded from remote cortical areas and are supposed to reflect orthodromic propagation of the stimulus signal through the cortico-cortical connections (Matsumoto R et al. 2017; Matsumoto R and T Kunieda 2018). This method was first applied for patients with implanted subdural electrodes, which successfully delineated various functional cortical networks (Matsumoto R et al. 2004; Lacruz ME et al. 2007; Conner CR et al. 2011; Koubeissi MZ et al. 2012; Swann NC et al. 2012; Kubota Y et al. 2013; Matsuzaki N et al. 2013; Keller CJ, CJ Honey, P Megevand, et al. 2014; Enatsu R et al. 2015; Usami K et al. 2018). The connectivity pattern retrieved as CCEPs overlaps in large part with the resting-state functional connectivity measured by resting-state fMRI (Keller CJ et al. 2011; Keller CJ, CJ Honey, L Entz, et al. 2014). Due to its high practicality and reproducibility, CCEP has been clinically utilized to probe and monitor the connectivity of the AF during neurosurgical operations (Saito T et al. 2014; Yamao Y et al. 2014; Yamao Y et al. 2017) to ensure speech preservation (what we call “intraoperative CCEP” examination).
To investigate the patterns of connectivity from the IFG to the temporoparietal area, we systematically applied single-pulse stimulation to three IFG subdivisions (pOrb, pTri, and pOpe) and recorded CCEP responses in an intraoperative setting. Although the connectivity between the posterior IFG and the inferior parietal area and the posterior temporal area has been intensively studied (Greenlee JD et al. 2004; Matsumoto R et al. 2004; Greenlee JD et al. 2007; Garell PC et al. 2013; Yamao Y et al. 2014), this study is unique in that we visualized and analyzed the spatiotemporal dynamics of CCEP connectivity from all the IFG subdivisions, in particular from the anterior IFG, in light of the dual-stream model of language processing.
Materials and Methods
Participants
Fourteen patients (7 male, age 45.9 ± 17.2) were recruited for this study. The patient demographics are shown in Table 1. These patients were selected according to the following criteria from the 49 consecutive patients who underwent surgical resection of a cerebral lesion in the language-dominant hemisphere between March 2014 and July 2016. All the selected patients were supplied with the appropriate information about the study, provided written informed consent, and received intraoperative CCEP. The inclusion criteria were as follows: (1) the stimulus sites of the CCEP investigation covered all three subdivisions of the IFG (pOrb, pTri, and pOpe), which was confirmed by intraoperative photographs of the grid electrodes; (2) the recording electrodes covered the lateral temporo-parietal area; (3) no invasion or severe mass effect was observed in the temporal stem or extreme capsule, where the fibers of the ventral stream converge. See Figure 1.
In 11 patients, the language-dominant hemisphere was determined by the Wada test with intra-carotid administration of propofol (Takayama M et al. 2004). In two patients (patients 4 and 5), the Wada test was omitted because of the urgent clinical situation, and language fMRI was used instead to define the dominant hemisphere (Yamao Y et al. 2014). One patient (patient 2) could not perform any language tasks because of motor aphasia resulting from the tumor, indicating that the affected hemisphere was language dominant. Intraoperative CCEP investigation was performed to monitor the integrity of the dorsal language pathway during surgery. The clinical usefulness of monitoring the dorsal language pathway was reported in the previous literature (Yamao Y et al. 2014).
This study was approved by the Ethics Committee of Kyoto University Graduate School and the Faculty of Medicine (IRB C573, C443, and C1082).
Preparation and acquisition of intraoperative CCEP data
In all patients, the craniotomy was performed under general anesthesia. After the dura was opened, one grid electrode was placed on the frontal lobe to cover the anterior language core (Broca’s area) and another one or two grid electrodes were placed on the tempo-parietal cortices to cover the posterior language core (Wernicke’s area). The location of electrodes was always determined by clinical need (that is, monitoring of CCEP and functional mapping).
For the preoperative planning of grid placement, anatomical and functional images were acquired with a 3-Tesla magnetic-resonance scanner (Trio, Siemens, Erlangen, Germany) as described elsewhere (Yamao Y et al. 2014; Yamao Y et al. 2017). We constructed a cortical surface model from the T1-weighted image using FreeSurfer software (https://surfer.nmr.mgh.harvard.edu/).
The electrodes were made of platinum with a recording diameter of 3 mm and a center-to-center distance of 1 cm (Unique Medical Co., Ltd., Tokyo, Japan). The details of CCEP recording have been reported elsewhere (Matsumoto R et al. 2004; Matsumoto R et al. 2007; Matsumoto R et al. 2012; Yamao Y et al. 2014). A 32-channel intraoperative monitoring system (MEE 1232 Neuromaster, Nihon-Kohden, Tokyo, Japan), equipped with an electrical stimulator (MS-120B, Nihon-Kohden, Tokyo, Japan) was used for generating single pulses for stimulation, for recording the raw electrocorticogram (ECoG), and for online analysis of the averaged CCEP waveform. The raw ECoG data were recorded at a sampling rate of 5 kHz. Recordings from subdural electrodes were referenced to a scalp electrode placed on the skin over the mastoid process contralateral to the side of craniotomy.
Single-pulse electrical stimulation was applied in a bipolar fashion using a pair of adjacent electrodes. Square-wave electrical pulses of alternating polarity with a pulse width of 0.3 ms were delivered at 1 Hz. We fixed the stimulation intensity at 15 mA to shorten the investigation time since we did not have enough time to adjust the stimulus intensity in every session in the operating room. The stimulation order was as follows: First, we stimulated all possible electrode pairs in the IFG while recording the CCEP responses in the temporo-parietal area. We then stimulated selected temporo-parietal electrodes, namely, those with discrete CCEP responses to IFG stimulation, to investigate the reciprocal connectivity. All the CCEP responses analyzed in this study were recorded under general anesthesia. CCEP examination under general anesthesia was feasible since the distribution of the CCEP response did not change even though the amplitude of maximum response becomes slightly larger in the awake state (Yamao Y et al. 2014).
The online CCEP analysis was obtained by averaging the ECoGs (30 trials in each session) across time windows phase-locked to stimulation, each with a post-stimulus duration of 200 ms and a pre-stimulus baseline of 20 ms. We checked the reproducibility of the response in at least two sessions to distinguish the CCEP responses from baseline activities. The raw ECoG was simultaneously recorded and displayed to monitor seizure patterns during stimulation. The online CCEP analysis was used to determine the stimulation electrodes to be used for testing reciprocal connectivity. The recorded raw ECoG data were used for further offline analysis. The offline analysis was obtained by averaging ECoGs phase-locked to the stimuli (30 trials per session) with a time window of 300 ms and a baseline of 30 ms before stimulus onset.
Visualization of the spatiotemporal dynamics of the CCEP: the 4D CCEP map
Obtaining a clear understanding of the whole connectivity pattern just from an inspection of the waveforms of individual patients is difficult because the electrode locations differ by patient. To understand the spatiotemporal dynamics based on the data derived from all patients, we created a “4D CCEP map,” that is, a 4D (time-sequence of 3D) volume image in the Montreal Neurological Institute (MNI) standard space, creating one such map for each stimulus area in the IFG (pOrb, pTri, and pOpe). For each time point (time-locked at a stimulation), all amplitude data were plotted in the MNI space, averaged and smoothed with a Gaussian kernel (see Supplementary Materials for detailed procedures.) Uneven electrode coverage was corrected by dividing the summed amplitudes by the number of measurements. To visualize the 4D representation of the CCEP, we digitally rendered a standard brain-surface model, providing each vertex with the value at the nearest-neighbor voxel in the 4D CCEP map. The time sequence of this rendered brain surface was presented as a movie. (Available in the Supplemental Data.)
Topographical analysis of frontotemporal connectivity
To clarify the spatial relationships between the stimulus and response sites, we performed a linear regression analysis on their coordinates, which we term the “topographical analysis” of the CCEP. First, we determined the CCEP response by visual inspection of the waveforms with the following criteria:
The polarity is negative.
The amplitude is larger than 6 × the standard deviation (SD) of the baseline fluctuations. The baseline is defined as the period between 100 ms and 5 ms pre-stimulus.
The response is reproducible across two consecutive sessions. (30 trials are averaged for each session.)
We excluded data from electrodes located within 25 mm of the stimulus site to rule out responses due to local U-fibers since our objective was to investigate the long-range CCEP responses. Volume-conducted responses, although rare in areas > 25 mm distant, were eliminated by visual inspection because they putatively reflect large responses just under the stimulus area (Shimada S et al. 2017). We judged responses to be volume-conducted when the waveforms were almost invariant in shape and diminished steadily with distance from the stimulus site. After we inspected all the recorded waveforms to determine the early and delayed CCEP responses, the basic properties of the CCEP responses such as onset time, peak time and amplitude were stored in a database (referred to hereafter as the CCEP database) together with the MNI coordinates of the electrodes. We classified each response as early (N1) or delayed (N2) by a cluster analysis of the latency distribution (see Figure S1), although the N1 cluster determined in this method was similar to the traditional criteria of N1 (onset < 30 ms, peak < 100 ms).
Although we judged the CCEP response based solely on single waveforms, traditional waveform analysis has paid attention to locally maximal responses that seem to be the center of the response when adjacent electrodes show a similar waveform. To perform a similar analysis in this study for purposes of comparison, we identified maximum response sites in the CCEP database automatically using a MATLAB script written in-house. We defined a “max response” site as one that had the largest amplitude in the spatio-temporal neighborhood, where spatial proximity means within 15 mm of the inter-electrode distance and temporal proximity means within 5 ms of the peak time difference.
After collating the CCEP database, we investigated whether the spatial distribution of N1 responses in the temporo-parietal area differs according to the stimulus site in the IFG. Because the distribution of the response sites is parallel to the y-z plane, we verified the difference in the two-dimensional distribution (of MNI y and z coordinates) using the Wilk’s lambda test. We also evaluated the hypothesis that the more anterior the location of the stimulus site (in IFG), the more anterior is the response site (in the lateral temporal cortices). We created new coordinates for the stimulus and response sites, separately. We measured the distance between the stimulus site and the midpoint of the lower third of the precentral sulcus (see the left panel of Figure 4C) for the stimulus sites. We performed principal-component analysis for all the N1 response sites and extracted the anterior-posterior axis parallel to the temporal gyri as the first component (which we named Y1; See Figure 4C) for the response sites. The second component indicates the direction perpendicular, i.e. in a dorso-ventral temporal lobe orientation, to Y1 (named Y2). We performed linear regression analysis of X and Y1 or Y2.
Analysis of fronto-parietal connectivity
As the number of cases that cover the parietal area is small and statistical analysis as above is not feasible, we only described the area-to-area connectivity by detecting the maximum response electrodes in each CCEP examination. We intended to perform a similar topographical analysis between the IFG and parietal lobe. Here, we focused on pOrb connectivity to the inferior parietal area as investigated by pOrb stimulation, since previous literature has reproducibly reported the CCEP connectivity between pOpe/pTri and the inferior parietal area (Matsumoto R et al. 2012; Entz L et al. 2014; Keller CJ, CJ Honey, P Megevand, et al. 2014; Yamao Y et al. 2017)
Probing reciprocal connections from and to the pars orbitalis
We investigated the reciprocality of the connections from pOrb rather than pTri or pOpe because the latter has already been investigated in our previous reports using a different patient population (Matsumoto R et al. 2004; Yamao Y et al. 2017). We considered connectivity to be reciprocal when stimulation through the temporal (or parietal) response electrode evoked a max response in at least one of the paired stimulus electrodes in the IFG pOrb. Technical details regarding this procedure are provided as supplementary data. We calculated the reciprocality rate for six groups of stimulus-recording pairs stratified by area (fronto-temporal vs. fronto-parietal) and type of response (max response, any response, or no response). We treated the stimulus-recording pair with no CCEP response equally as those with a CCEP response in order to obtain the negative controls.
Comparison with resting-state fMRI (rs-fMRI) connectivity
We compared the CCEP connectivity originating from the IFG pOrb with the functional connectivity revealed by the rs-fMRI for the purpose of validation. We utilized the functional connectivity maps available from the NeuroSynth website (http://neurosyngh.org/) derived from 1000 healthy subjects as a reference. For each stimulus site in IFG pOrb, a functional connectivity map was obtained from the website as a 3D volume image by specifying the stimulus coordinate as the seed voxel. We calculated the voxel-wise average of all functional connectivities obtained as described above as one volume image. We subsequently visualized the averaged connectivity map as a color map on the standard brain surface and compared it with the CCEP map by visual inspection.
Results
Visualization of distinct connectivity patterns from IFG subdivisions
The CCEP connectivity pattern varied distinctly when stimulation was administered through different subdivisions of the IFG. As shown in a representative case (Figure 2), the distribution of the CCEP response changed depending on whether the stimulation was applied through the pOpe, pTri or pOrb. In each patient, we observed distinct connectivity patterns for different IFG subdivisions. However, it is difficult to deduce a general rule of connectivity directly from individual cases due to limitations and variations in electrode coverage peculiar to each subject. Therefore, to systematically visualize the CCEP connectivity, we combined all patient data into a standardized map of connectivity between the IFG and the lateral temporoparietal cortices.
Figure 3 shows the averaged response map obtained by stimulation of the three subdivisions in IFG. The 4D CCEP movie (provided as a supplemental data) demonstrates the time course of the CCEP amplitude distribution. The waveforms in Figure 3 represent the averaged temporal dynamics of the voxels included in each ROI. The center of the four spherical ROIs were located at the representative N1 (early negative) response areas in IFG stimulation: “R1” was set on the N1 response area of pOrb stimulation; “R2” and “R3,” on that of pOpe and pTri; and “R4,” on that of the stimulation in the three subdivisions. As the movie and the waveforms show, pOpe stimulation elicited prominent N1 responses in the posterior part of the temporal lobe (STG and middle temporal gyrus [MTG]) and adjacent parietal areas (supramarginal gyrus [SMG] and angular gyrus [AG]) around 30 ms after stimulus onset. After the N1 response, a larger and broader negative response (N2) with a peak latency of 150–200 ms was evoked in each response area (R2, R3, and R4). Though the averaged waveform suggests that the inferior part of the anterior lateral temporal lobe (R1) exhibited an N1 response for pOpe stimulation, we regarded this activity as a far-field potential reflecting the large response around the stimulus site; the R1 response shares the temporal dynamics of those electrodes around the stimulus site in the early phase (< 20 ms), as is demonstrated in the 4D CCEP movie. In contrast, pOrb stimulation elicited an N1 response in the anterior part of the ITG and MTG at around 40 ms after stimulation followed by a larger N2 response in the same area (see the averaged waveform of R1 in the lower panel of Figure 3). It also elicited an N1 response in the ventral part of the AG, followed by a large N2 response in the same area (see the averaged waveform of R4 in the lower panel of Figure 3). pTri stimulation showed a response pattern intermediate between those of pOpe and pOrb stimulation since its CCEP response locations comprised the posterior STG, the posterior MTG, and the AG (N1 and N2), which resemble those of pOpe stimulation, and the anterior MTG and ITG (N2), which resembles those of pOrb stimulation.
Topographical analysis of frontotemporal connectivity
To statistically validate the differences in connectivity pattern visualized with the 3D average response map, we investigated the topographical distribution of the early negative (N1) responses (Figure 4A, B). In pOrb stimulation, the N1 response sites clustered in the anterior inferior part of the lateral temporal area. On the other hand, in pOpe stimulation, the N1 response sites clustered in the posterior part of the lateral temporal area. Stimulation of pTri elicited N1 responses at sites between the former two clusters. The spatial distribution was significantly different between any pair of the three parts, pOrb, pTri, and pOpe by Wilk’s lambda, p < 0.01. When the scatter plot was confined to the max response sites for N1, the statistical differences remained significant (Figure 4B).
The finding that pTri stimulation showed a connectivity pattern intermediate between those of pOpe and pOrb stimulation implied a gradient in the connectivity pattern revealed by IFG stimulation. We performed a linear regression analysis based on the coordinates of stimulus sites and response sites. The locations of the stimulus sites were linearly correlated with those of the N1 max response sites in the lateral temporal area (Figure 4C). In the anterior-posterior axis, the regression line could be calculated both in each temporal gyrus (STG, Y = 2.37 × X - 56.27, R2 = 0.61, p = 0.013; MTG, Y = 1.12 × X - 28.77, R2 = 0.34, p = 0.003; and ITG, Y = 0.43 × X - 3.59, R2 = 0.53, p = 0.017) and in the whole temporal cortex (Y = 0.88 × X - 20.29, R2 = 0.32, p < 0.0001). On the other hand, no significant correlation was observed in the superior-inferior axis. In summary, the more anterior part of the IFG connects to the more anterior part of the lateral temporal area, while the more posterior IFG connects to the more posterior temporal area, indicating a connectivity gradient along the anterior-posterior axis. We also analyzed all response sites instead of maximal response sites and observed a similar gradient of connectivity supported by linear regression analyses.
Fronto-parietal connectivity
The averaged response map clearly demonstrated the connectivity between each IFG subdivision and the inferior parietal area. In the present study, pOrb stimulation elicited discrete parietal CCEP responses in three of five patients who had a grid on the parietal lobe (Figure 5). In all three patients, pOrb stimulation elicited early negative (N1) response in the AG, while pTri or pOpe stimulation elicited N1 response in the SMG. The N1 peak latency in the inferior parietal area was always longer in pOrb stimulation than in pTri and pOpe stimulation, as shown by the following data: patient 1, 45 ms (pOrb stimulation, AG) vs. 31 ms (pTri stimulation, SMG) and 37 ms (pTri stimulation, SMG); patient 9, 43 ms (pOrb stimulation, AG) vs. 31 ms (pTri stimulation, AG) and 34 ms (pOpe stimulation, SMG); patient 14, 34 ms (pOrb stimulation, AG) vs. 27 ms (pTri stimulation, SMG) and 31 ms (pOpe stimulation, SMG).
Reciprocality
We investigated the occurrence rates of reciprocality in the connections between the IFG pOrb and the temporal and parietal areas (Table 2). We stimulated pOrb through a total of 41 stimulus sites and observed an anterograde CCEP response in 52 electrodes in the temporal area. Among them, 22 electrodes showed a max response. Due to limitations of time in the operating room, we were able to stimulate only 36 electrode pairs that included at least one of the anterograde response sites, and observed 25 “reciprocal” connections (25/36 = 69.44%) with max retrograde responses at the “initial” stimulus site. When the analysis is confined to max anterograde response sites, we were able to stimulate 18 electrode pairs that included at least one of the anterograde max response sites, and observed 13 reciprocal connections (13/18 = 72.22%). We performed a similar analysis of the no-response electrodes as a negative control. We aggregated all CCEP recordings that included at least one no-response electrode (333 total), and among them, we found 30 reciprocal connections (30/333 = 9.01%). The occurrence rate of reciprocal connections was significantly higher at max response sites or at all response sites than at no-response sites (unpaired t-test, p < 0.0001, uncorrected).
We performed a similar investigation on the connectivity between pOrb and the parietal area and observed similar results, although the numbers were smaller: 3 reciprocal responses upon stimulation of 7 max anterograde response sites (3/7 = 42.86%), 6 reciprocal responses upon stimulation of 11 anterograde response sites (6/11 = 54.55%), and 8 reciprocal responses upon stimulation of 93 no-response sites (8/93 = 8.60%). The occurrence rate was significantly higher in both maximal response sites and all response sites than in no-response sites (unpaired t-test, p < 0.05, uncorrected).
Latency and estimated conduction velocity
Table 3 shows the onset times and peak latencies of all measured waveforms. In the lateral temporal cortices, the N1 onset latency was significantly longer with pOrb stimulation than with pTri or pOpe stimulation (unpaired t-test, p < 0.005, uncorrected). The peak latency was longer with pOrb stimulation than with pOpe stimulation (unpaired t-test, p < 0.005). Similarly, in the inferior parietal lobule, pOrb stimulation showed longer latencies at onset and peak than did the other two subdivisions, although the number of available pOrb stimulations was small (n = 5).
We plotted the onset latency vs. the Euclidean distance between the stimulus and response sites to investigate conduction velocity (see Supplemental Figure S2.) The slope of the regression line (Y = 0.076 × X + 8.2) indicated an approximate conduction velocity of 13.2 m/s (p < 0.05), with large variability (R2 = 0.047). We also made scatter plots for each stimulus area (pOrb, pTri, and pOpe) to compare conduction velocity among them, but no significant regression lines were found.
Comparison with resting-state functional connectivity
The connectivity pattern elicited by stimulation of pOrb was generally similar to that of the resting-state functional connectivity obtained from the NeuroSynth database by specifying the seed as a stimulus site in IFG pOrb (Figure 6A, B). The distribution was similar between the two connectivity modalities in the anterior part of the ITG and MTG and in the inferior parietal lobule, while a difference was observed in the posterior part of the MTG (rs-fMRI positive, CCEP negative). The discrepancy is attributable to the presence of an indirect correlation via the posterior IFG (pTri and pOpe) for rs-fMRI connectivity, because pTri showed strong correlation with both pOrb and the posterior MTG. Because the resting-state functional connectivity is a measure of correlation, it inevitably visualizes a chain of strong relationships as a single indirect relationship.
Discussion
Based on a compilation of CCEP data, we investigated the connectivity pattern between the IFG and the temporoparietal area. The CCEP response pattern indicated a gradual transition of connectivity from stimulus sites in the posterior IFG (pOpe) to those in the anterior IFG (pOrb). Topographical analysis of stimulus and response sites confirmed the presence of a connectivity gradient between IFG and the temporal lobe along the anterior-posterior axis. In particular, the anterior part of the IFG (pOrb) showed connectivity to the anterior lateral temporal area, which has not been well delineated by frozen-dissection, although a recent study utilizing probabilistic tractography demonstrated the connectivity between the pOrb and the lateral surface of the rostral temporal lobe (Binney RJ et al. 2012). We discuss the functional and clinical aspects of these results below.
Candidate white matter pathways between the anterior IFG and temporal lobe
The present CCEP findings revealed connections between the anterior IFG (pOrb) and the anterior lateral temporal lobe. Although CCEP does not provide direct evidence about the underlying white-matter pathways, recent in vivo and post-mortem anatomical studies utilizing diffusion tractography and frozen dissection (Klinger’s method) potentially yield some clarification of the white-matter fibers terminating in the IFG. They consistently find that the anterior part (pOrb) and the posterior part (pTri and pOpe) of the IFG receive distinct fibers. That is, pOrb receives the termination of the IFOF (especially the superficial component) and UF, while pTri and pOpe receive terminations from the SLF and AF (Catani M et al. 2005; Barrick TR et al. 2007; Glasser MF and JK Rilling 2008; Lawes INC et al. 2008; Vassal F et al. 2016). Based on these anatomical findings, it seems plausible that upon pOrb stimulation, the electrical impulse is conveyed through the IFOF or UF, rather than the SLF or AF, to the anterior lateral temporal lobe. A different connectivity pattern from each IFG subdivision was also indicated by probabilistic tractography (Anwander A et al. 2007). That study demonstrated that the connectivity signature originating from pOpe represented the AF, while that from pOrb represented the UF and IFOF. As both structures pass through the extreme capsule in the temporal stem, we expect the existence of a pathway between the IFG pOrb and the anterior lateral temporal lobe via the extreme capsule. Since the UF mainly terminates in the temporal pole, which was not covered by the electrode grids in this study, the connectivity between the IFG pOrb and the anterior lateral temporal lobe implies the existence of the temporal branch of the IFOF, which we referred to as IFOF-t. The bundle comprised of the UF and IFOF-t can be depicted as a fan-shaped structure spreading over the temporal lobe, as illustrated in the classical textbook by Dejerine J and A Dejerine-Klumpke (Figure 6D). Here, we call this structure the “frontotemporal radiation.”
Although the IFOF-t has not been found in recent frozen-dissection or tractography studies, the existence of such connectivity is supported by our finding of reciprocality for this connectivity (Table 2) and by similarity with the resting-state functional connectivity (Figure 6). The reciprocal connectivity under the discussion implies the functional relevance of the connectivity. The resemblance between CCEP connectivity and rs-fMRI connectivity validates the existence of connectivity, as the CCEP amplitude is reported to correlate with the rs-fMRI connectivity (Keller CJ, CJ Honey, L Entz, et al. 2014). Furthermore, in one recent study, where whole-brain deterministic tractography was performed and virtual dissection of the UF and IFOF by a novel “stem-based” approach was carried out, a fanning structure comprising the UF and IFOF was visualized, including what we call IFOF-t (Hau J, S Sarubbo, JC Houde, et al. 2016). The discrepancy between the CCEP and the frozen-dissection/tractography results is attributable to two points. One is the presence of small fiber diameters in the ventral pathway (UF and IFOF), as revealed in an electron microscopic investigation (Liewald D et al. 2014). The other is that, like all fibers running through the extreme capsule complex and temporal stem, the IFOF-t is closely bundled with many other, major long tracts (Martino J, F Vergani, et al. 2010; Peltier J et al. 2010; Ribas EC et al. 2015; Bajada CJ, B Banks, et al. 2017). In the frozen-dissection technique, the frozen white matter is peeled along the principal fiber direction, which means that small fibers running across the major direction are destroyed (Zemmoura I et al. 2016). The tractography technique is based on the direction of local water diffusivity, which represents the principal direction of fibers within the voxel, and will, therefore, neglect the small crossing fibers (Tuch DS et al. 2003; Mukherjee P et al. 2008). CCEP relies on neurophysiological measurement, and thus makes it a more sensitive method for tracing crossing fibers.
Candidate white matter pathways between the anterior IFG and the parietal lobe
In the present study, pOrb stimulation elicited discrete responses in the parietal area, and stimulation at the response sites revealed reciprocal connections. Based on the above discussion, pOrb stimulation is assumed to propagate through the IFOF. In the parietal termination, CCEP responses were found predominantly in the AG, which is known to be one of the posterior terminations of the IFOF (Caverzasi E et al. 2014; Hau J, S Sarubbo, G Perchey, et al. 2016). We cannot exclude the possibility that anterior IFG-AG connectivity is mediated by the SLF III because this tract is also reported to project to the AG and anteriorly as far as the dorsolateral prefrontal cortex (Mars RB et al. 2011; Seghier ML 2013; Parlatini V et al. 2017). However, to the best of our knowledge, there has been no report proving that the frontal termination of the SLF III clearly includes the IFG pOrb.
Longer latencies of CCEP with stimulation in pOrb
The relatively long onset latency of CCEP responses seen with pOrb stimulation is consistent with the existence of the IFOF-t, since, in an electron microscopic investigation, the fiber diameter of the ventral pathway (UF and IFOF) was found to be smaller than that of the dorsal pathway (SLF) (Liewald D et al. 2014) and conduction velocity is well known to increase linearly with fiber diameter (Hursh JB 1939). The longer response latency seen with pOrb stimulation is also consistent with the fact that pOrb showed a lower myelin density than pTri or pOpe in recent myelin-density mapping studies (Glasser MF and DC Van Essen 2011; Glasser MF et al. 2016). The observation of a lower myelin density supports the possibility that the axons originating in the area are less myelinated and therefore have lower conduction velocities than those from pTri or pOpe.
A connectivity gradient in the IFG
The linear regression analysis based on the coordinates of the stimulus and response sites indicated that the IFG is connected to the lateral temporal cortex with a gradation in the anterior-posterior axis. It is not only consistent with the presence of a fan-shaped structure, but also implies a seamless transition from the dorsal stream to the ventral stream in the IFG. Recently, a functional and connectivity gradient along the anterior-posterior axis were found not only in the IFG (Hagoort P 2005; Xiang HD et al. 2010; Udden J and J Bahlmann 2012; Thiebaut de Schotten M et al. 2016) but also in the temporal lobe (Bajada CJ, RL Jackson, et al. 2017; Jackson RL et al. 2018). Interestingly, in both, the anterior part was associated with a modality-general network and the posterior part with a modality-specific network. As Figure 6C shows, our results supported the graded functional differentiation in the IFG. Although the concept of a connectivity gradient appears in previous literature, this is the first report of an anterior-posterior gradient in the temporal projection from the IFG based on an electrical tracing method. Here, again, the gradual nature of the CCEP connectivity agrees with the fanning structure illustrated in the historical textbook, since the fan-shaped bundle of lines was drawn not only in the anterior part but also in the posterior part of the IFG (Figure 6D).
Possibility of parcellation based on the CCEP connectivity
Our CCEP data indicated not only the existence of the two functional networks in the IFG but also the possibility of parcellation based on the CCEP connectivity. Though we can find numerous reports on the connectivity-based parcellation of human brain by means of DTI (Anwander A et al. 2007; Cloutman LL and MA Lambon Ralph 2012) and rs-fMRI (Arslan S et al. 2018; Jackson RL et al. 2018; O’Muircheartaigh J and S Jbabdi 2018), to the best of our knowledge, there are no reports on that of CCEP connectivity, though there have been reports of the whole brain connectivity matrix (ROI analysis based on template) collecting individual CCEP data (Entz L et al. 2014; Donos C et al. 2016). As we showed at the individual level (Figure 2) and in the group average level (Figure 3), a 1 cm difference in the stimulus site resulted in a totally different connectivity pattern and the average connectivity pattern was different for each stimulus area in the IFG. Compared to the MRI-based methods, which make use of the whole brain connectivity data, the CCEP-based parcellation seems to be difficult since the spatial resolution is no better than MRI and the CCEP data is collected only beneath the implanted electrodes. However, the CCEP-based method takes advantage of CCEP, which is based on direct electrical stimulation and is free of disadvantages such as artifacts caused by edema or tumors in MRI. Especially for such an eloquent area as the IFG on the dominant side, the CCEP connectivity-based parcellation is clinically important because it enables functional mapping without requiring the patient’s conscious cooperation as is often the case with children or patients with cognitive disturbance. Although these results must be verified with a larger population, the present study proved that the parcellation of a functionally confluent area such as the IFG solely by CCEP is feasible.
Functional implications of the connectivity determined from pOrb
The present study demonstrated that visualizing the connectivity from the anterior part of the IFG to the anterior part of the MTG/ITG is feasible by the CCEP methodology. As discussed above, both the frontotemporal and the frontoparietal connectivity from pOrb are considered to be mediated by subcomponents of the IFOF. From a functional point of view, the IFOF is reported to have a semantic function as evidenced by intraoperative electrical stimulation at subcortical white-matter sites along the IFOF (Duffau H 2005). IFOF-t also seems to be involved in a semantic function according to the following pieces of evidence at its cortical terminations. The anterior IFG, which is the frontal termination of the IFOF-t, has been revealed by means of fMRI to engage in controlled semantic retrieval (Wagner AD et al. 2001; Krieger-Redwood K et al. 2015), and TMS in this area prolonged the response latency in a synonym judgement task (Gough PM et al. 2005; Hoffman P et al. 2010). With regards to the cortical termination in the temporal lobe, a PET activation study in healthy subjects revealed the involvement of the anterior MTG and ITG in comprehension of words presented auditorily and visually (Spitsyna G et al. 2006) and studies using voxel-based lesion-symptom mapping in aphasic patients found associations with semantic error in the lateral anterior temporal cortex (Walker GM et al. 2011). It appears likely that the network between these two regions, namely the IFOF-t, has a role in semantic processing.
We also determined the connectivity between pOrb and the AG, although the number of patients was small (Figure 5). As mentioned previously, tractography shows that the AG is connected with the pOrb, via the parietal branch of IFOF (Caverzasi E et al. 2014; Hau J, S Sarubbo, G Perchey, et al. 2016), which was confirmed by frozen-dissection (Curran EJ 1909; Martino J, C Brogna, et al. 2010). Just like pOrb, the AG is associated with a semantic role, as is proposed by meta-analysis of neuroimaging studies focusing on semantic processing (Binder JR et al. 2009), though the behavior of AG during task fMRI is significantly different from that of ATL (Humphreys GF et al. 2015), which is the semantic representational hub, as evidenced by a TMS study (Hoffman P et al. 2010). The facts that both the pOrb and AG are associated with semantic processing implies that the parietal branch of the IFOF may be associated with semantic processing. Even when looking outside the semantic network, a direct connection between them deserves attention because not only the AG but also the anterior IFG is involved in the default mode network (Buckner RL et al. 2008).
Clinical implications of the CCEP examination in IFG
Previous reports from our group showed that the intraoperative CCEP with stimulation of pTri and pOpe is clinically useful to probe the posterior language area (Wernicke’s area) through AF (Yamao Y et al. 2014). The present study extended its clinical implication to map the whole connectivity along the anterior-posterior axis of the IFG. The graded connectivity along the IFG and the temporal lobe underlies the functional gradient in both areas as discussed above: the more anterior region connects to the more modality-general and the more posterior to the more modality-specific. This comprehensive IFG connectivity mapping would allow delineating the functional regions located in the anterior part of the IFG and temporal lobes, such as the semantic control area. In the future, we could refer to the “4D CCEP map” to guide the location of electrode placement, when more patients are enrolled to refine its quality for clinical practice.
In this study, we could not map the cortical functions in the anterior part of the IFG and the temporal lobe during awake surgeries. To investigate the semantic function, administration of specialized tasks for semantic cognition will be required. Such deliberate tasks will be more time-consuming than intraoperative tasks such as picture naming, and will demand more attention and motivation from the patients, which is difficult to achieve in intraoperative settings. Mapping studies in patients with chronically implanted electrodes for epilepsy surgery will delineate more deliberate cognitive functions in these areas. We believe mapping and preserving these higher functions out of the classical “eloquent” area such as the Broca’s area would improve the quality of life for patients undergoing neurosurgeries. In order to preserve the white matter pathway such as the temporal stem, intraoperative sequential CCEP evaluation would be clinically beneficial for patients who have lesions in the insula or the temporal stem. Detailed longitudinal neuropsychological assessments of language and semantic function warrants the functional relevance of these cortical and subcortical areas for neurosurgery.
Study limitations and conclusion
This study investigated and clearly illustrated the connectivity between the IFG and the temporoparietal area. However, some limitations should be noted.
First, we cannot absolutely exclude the pathological effect of the lesion, though we excluded patients who had lesions or massive edema around the temporal stem, the key structure of the ventral language network.
Second, the location of the electrodes was determined by the clinical requirements of monitoring language function and the safety issues. For example, electrode grids are placed on a flat surface for stability and for keeping a distance from bridging vessels for safety. To compare the connectivity patterns among all the three subdivisions in the IFG, we included only those patients where all the three IFG subdivisions were covered by electrodes.
Third, this study lacks direct evidence on the white matter underpinning connectivity between the anterior IFG and the anterior MTG/ITG. If we observe an evoked potential in both terminals (the pOrb and the anterior MTG/ITG) by a single-pulse electrical stimulation on the white matter, it would provide proof of underpinning. Actually, we tried the stimulation of IFOF on the superior wall of the inferior horn through the removal cavity using a 1 × 4 strip electrode after anterior temporal lobectomy. However, the result was widespread CCEP responses in almost all frontal and temporal electrodes, which made interpretation difficult (unpublished data). At present, we have no direct evidence though a smaller electrode and a weaker intensity of the stimulus may improve the situation.
Fourth, this study includes no functional mapping of connectivity as mentioned in the previous section. Further studies are expected to assess the function of the connectivity observed here using electrical stimulation of the white matter and the cortices in both terminals. These assessments should be included in future studies because we believe that it is necessary for future neurosurgeons to be aware of neural structure function within the operative field even if it is out of the classical “eloquent” area.
Last, the number of patients in the present study is smaller than in other studies that visualized connectivity using CCEP. Recently, several connectivity maps based on a larger population of patients with implanted electrodes have been published (Entz L et al. 2014; Donos C et al. 2016; Trebaul L et al. 2018). Although our study includes a relatively small number of patients, it is noteworthy that all our patients had single pulse stimulation in all subdivisions of the IFG available for the observation of differences in connectivity patterns and that all data were collected within one institute, which eliminates concerns about differences in stimulus parameters and the measurement environment.
Our intraoperative CCEP data showed that the anterior IFG is connected to the anterior MTG/ITG. Combined with prior anatomical knowledge about the frontal termination of language-related fibers, these results show that the anterior IFG has a connection with the anterior MTG/ITG through the ventral stream (referred to herein as the IFOF-t) that appears as a fan-shaped structure, here named the “fronto-temporal radiation,” together with the UF and the classical IFOF. The anterior-posterior gradient in the connectivity we observed between the IFG and the temporal area suggests the presence of a gradual transition in IFG efferents between the ventral stream and the dorsal stream.
Funding
This work was partly supported by the Grant-in-Aid for Scientific Research by the Ministry of Education, Culture, Sports, Science, and Technology (grant numbers 25861273, 26282218, 15H05874, 15K10361, 16K19510, 17H06815, and 17K10892). MALR was supported by a programme grant from the Medical Research Council, UK (MR/R023883/1).
Acknowledgments
We thank Drs. Tamaki Kobayashi, Taku Inada, Yuki Takahashi, Sei Nishida and Rika Inano for their cooperation in the intraoperative CCEP examination. The Department of Epilepsy, Movement Disorders, and Physiology, Kyoto University Graduate School of Medicine conducts Industry-Academia Collaboration Courses, supported by Eisai Co., Ltd., Nihon Kohden Corporation, Otsuka Pharmaceutical Co., and UCB Japan Co., Ltd.