Sound identification in human auditory cortex: Differential contribution of local field potentials and high gamma power as revealed by direct intracranial recordings
Introduction
Intracranial recordings (electrocorticography or ECoG) have become crucial for identifying the functional organization of human auditory cortex due to their high spatial and temporal resolution (e.g. Mukamel and Fried, 2012, Nourski and Howard, 2015). ECoG is a rich time-varying measure that simultaneously reflects synaptic activity and action potentials from populations of neurons. Consequently, there is considerable interest in exactly which aspects of the ECoG signal recorded from the auditory cortex carry information relevant to sound processing. Addressing this is not only important methodologically but may also hint at fundamental ways in which populations of neurons code information.
Earlier studies using the intracranial methodology relied on analysis of time domain-averaged local field potential (LFP) signals to examine response properties of auditory cortex (e.g. Celesia and Puletti, 1969, Halgren et al., 1995, Howard et al., 2000, Lee et al., 1984, Liégeois-Chauvel et al., 1994, Liégeois-Chauvel et al., 1991, Steinschneider et al., 1999). The averaged LFP (i.e., averaged evoked potential, AEP) emphasizes relatively low-frequency components of the ECoG signal that are both time- and phase-locked to the stimulus. This approach was in part aimed at identifying cortical generators of specific components of AEPs recorded using electroencephalographic methods and neuromagnetic fields recorded using magnetoencephalography in response to sound stimuli (e.g. Halgren et al., 1995, Howard et al., 2000, Liégeois-Chauvel et al., 1994).
With few exceptions (e.g., Chang et al., 2010, Sahin et al., 2009, Sinai et al., 2009, Steinschneider et al., 2011), more recent studies using intracranial methodology have focused on event-related band power (ERBP) of the high gamma frequency component (70–150 Hz) of the ECoG (e.g. Crone, Boatman, Gordon, & Hao, 2001). This approach often occurred at the expense of analysis of the time- and phase-locked activity as captured by the LFP. This paradigm shift has been driven by the findings that enhanced high gamma activity in the ECoG is closely related to increases in the blood oxygenation level-dependent signal as measured by functional magnetic resonance imaging methodology and to spiking activity in cortical neurons (Mukamel et al., 2005, Nir et al., 2007, Steinschneider et al., 2008). The focus on high gamma activity has yielded new understandings of the functional organization of human auditory and auditory-related cortex over the last decade. For instance, this analysis has helped characterize the functional representation of phonetic categories used in speech (Mesgarani et al., 2014, Pasley et al., 2012) and the powerful effects of selective attention in modulating auditory cortical activity when listening to competing speech streams (e.g., Mesgarani & Chang, 2012). Analysis of high gamma activity has also demonstrated tiered effects of attention across auditory and auditory-related cortical areas (Nourski et al., 2015, Steinschneider et al., 2014). All these findings parallel those obtained from patterns of spiking activity in experimental animals (e.g., Fritz et al., 2003, Mesgarani et al., 2008, Steinschneider et al., 2013, Tsunada et al., 2011). However, at the same time, the aforementioned advances have not compared the utility of LFPs and high gamma activity in understanding auditory processing.
This focus may be limiting because intracranially recorded LFPs have also helped characterize underlying features of functional organization of auditory and auditory-related cortex (e.g. Brugge et al., 2008, Chang et al., 2010). Furthermore, those studies that examined both high gamma and LFP revealed differences in the ways the two metrics are related to stimulus acoustics and perception (e.g., Nourski and Brugge, 2011, Nourski et al., 2009). These studies raise the possibility that both the LFP and high gamma ERBP in the ECoG reflect relevant (and non-redundant) information about sounds. If this is the case, it raises key questions about what information may be carried by the LFP that is not seen in the high gamma activity. What is needed is a direct comparison of the two measures of cortical activity to determine their relative contributions for carrying meaningful information about complex auditory stimuli as a whole.
In this study, we objectively examined this issue by using a classification approach. Subjects passively listened to consonant–vowel (CV) syllables and pure tone stimuli. The contribution of different measures of cortical activity for carrying information about these stimuli was assessed by training a classifier (support vector machine, SVM) to identify properties of the stimulus [voicing, place of articulation (POA), and tone frequency] on the basis of various permutations of the LFP and high gamma ERBP signal.
Under typical preparations, the LFP is usually a linear scaled voltage signal. It can be both positive and negative. In contrast, high gamma activity is usually a rectified power signal that is logarithmically scaled and baseline-normalized. Classification analysis can abstract across the differences between LFP and high gamma signal representation, as its dependent variable is classification accuracy (in percent correct) rather than a difference in the signal per se. Moreover, a non-parametric approach like an SVM may be better equipped for factoring out these differences than parametric approaches. It is important to note that the LFP signal is not orthogonal or independent of the high gamma signal, as they both are derived from the same underlying ECoG waveform. Our goal was not to try to parse out the unique information contained in each signal, but rather to use these coarse measures to ask if there is anything that cognitive neuroscience may be missing by relying on one over the other. To achieve this goal, we focused on typical preparations of these signals, characterizing the LFP as voltage time series, and high gamma activity as rectified, log-transformed and baseline-normalized ERBP.
Contrary to expectations, we found that classification accuracy based on LFPs was superior to that provided by high gamma activity. Best accuracy was often obtained when both measures were included in the analysis. Methodologically, this suggests that future studies should utilize neural activity captured both by the LFP and high frequency ERBP when investigating the functional organization of human auditory and auditory-related cortex; more broadly, it raises the possibility that by studying only local high gamma power we may be missing relevant aspects of sound encoding within the auditory cortex.
Section snippets
Subjects
Subjects consisted of 21 neurosurgical patient volunteers (16 male, 5 female, age 20–56 years old, median age 33 years old). The subjects had medically refractory epilepsy and were undergoing chronic invasive ECoG monitoring to identify potentially resectable seizure foci. Research protocols were approved by the University of Iowa Institutional Review Board and by the National Institutes of Health. Written informed consent was obtained from each subject. Participation in the research protocol did
Spatiotemporal properties of AEP and high gamma activity
CV syllables elicited robust evoked potentials and high gamma activity on PLST in both dominant and non-dominant hemispheres (Fig. 2, Fig. 3). Responses recorded from individual cortical sites appeared to be more distinct when comparing voiced and voiceless syllables (e.g. /ba, pa/) relative to the POA contrast (e.g. /ba, da/) (see Figs. 2B, 3B). For most of the subjects (of which the two shown here are representative) and for many recording sites, we found that both the initial positive and
Discussion
The goal of this study was to compare the information that can be extracted by two electrophysiological measures: the LFP and the high gamma band power. These comparisons should be interpreted as a comparison of standard methods for processing the electrophysiological signal; it is important to note that the LFP and high gamma power are not orthogonal measures of neural activity. Nonetheless, a classification approach using a non-parametric classifier can overcome some of these differences to
Acknowledgments
We thank Haiming Chen, Phillip Gander, Rachel Gold, and Richard Reale for help with data collection and analysis. This study was supported by NIH grants R01-DC04290, R01-DC00657, R01-DC008089 and UL1RR024979, Hearing Health Foundation, and the Hoover Fund.
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These authors contributed equally to this study.