An event-related fMRI study of overt and covert word stem completion

A Comparison of Denoising Approaches for Spoken Word Production Related Artefacts in Continuous Multiband fMRI Data

It is well-established from fMRI experiments employing gradient echo echo-planar imaging (EPI) sequences that overt speech production introduces signal artefacts compromising accurate detection of task-related responses. Both design and post-processing (denoising) techniques have been proposed and implemented over the years to mitigate the various noise sources. Recently, fMRI studies of speech production have begun to adopt multiband EPI sequences that offer better signal-to-noise ratio (SNR) and temporal resolution allowing adequate sampling of physiological noise sources (e.g., respiration, cardiovascular effects) and reduced scanner acoustic noise. However, these new sequences may also introduce additional noise sources. In this study, we demonstrate the impact of applying several noise-estimation and removal approaches to continuous multiband fMRI data acquired during a naming-to-definition task, including rigid body motion regression and outlier censoring, principal component analysis for removal of cerebrospinal fluid (CSF)/edge-related noise components, and global fMRI signal regression (using two different approaches) compared to a baseline of realignment and unwarping alone. Our results show the strongest and most spatially extensive sources of physiological noise are the global signal fluctuations arising from respiration and muscle action and CSF/edge-related noise components, with residual rigid body motion contributing relatively little variance. Interestingly, denoising approaches tended to reduce and enhance task-related BOLD signal increases and decreases, respectively. Global signal regression using a voxel-wise linear model of the global signal estimated from unmasked data resulted in dramatic improvements in temporal SNR. Overall, these findings show the benefits of combining continuous multiband EPI sequences and denoising approaches to investigate the neurobiology of speech production.

Decoding Single and Paired Phonemes Using 7T Functional MRI

Several studies have shown that mouth movements related to the pronunciation of individual phonemes are represented in the sensorimotor cortex. This would theoretically allow for brain computer interfaces that are capable of decoding continuous speech by training classifiers based on the activity in the sensorimotor cortex related to the production of individual phonemes. To address this, we investigated the decodability of trials with individual and paired phonemes (pronounced consecutively with one second interval) using activity in the sensorimotor cortex. Fifteen participants pronounced 3 different phonemes and 3 combinations of two of the same phonemes in a 7T functional MRI experiment. We confirmed that support vector machine (SVM) classification of single and paired phonemes was possible. Importantly, by combining classifiers trained on single phonemes, we were able to classify paired phonemes with an accuracy of 53% (33% chance level), demonstrating that activity of isolated phonemes is present and distinguishable in combined phonemes. A SVM searchlight analysis showed that the phoneme representations are widely distributed in the ventral sensorimotor cortex. These findings provide insights about the neural representations of single and paired phonemes. Furthermore, it supports the notion that speech BCI may be feasible based on machine learning algorithms trained on individual phonemes using intracranial electrode grids.

Neurophysiological evidence of motor preparation in inner speech and the effect of content predictability

Self-generated overt actions are preceded by a slow negativity as measured by electroencephalogram, which has been associated with motor preparation. Recent studies have shown that this neural activity is modulated by the predictability of action outcomes. It is unclear whether inner speech is also preceded by a motor-related negativity and influenced by the same factor. In three experiments, we compared the contingent negative variation elicited in a cue paradigm in an active vs. passive condition. In Experiment 1, participants produced an inner phoneme, at which an audible phoneme whose identity was unpredictable was concurrently presented. We found that while passive listening elicited a late contingent negative variation, inner speech production generated a more negative late contingent negative variation. In Experiment 2, the same pattern of results was found when participants were instead asked to overtly vocalize the phoneme. In Experiment 3, the identity of the audible phoneme was made predictable by establishing probabilistic expectations. We observed a smaller late contingent negative variation in the inner speech condition when the identity of the audible phoneme was predictable, but not in the passive condition. These findings suggest that inner speech is associated with motor preparatory activity that may also represent the predicted action-effects of covert actions.

Mapping cortical activations underlying covert and overt language production using high-density diffuse optical tomography

Gold standard neuroimaging modalities such as functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and more recently electrocorticography (ECoG) have provided profound insights regarding the neural mechanisms underlying the processing of language, but they are limited in applications involving naturalistic language production especially in developing brains, during face-to-face dialogues, or as a brain-computer interface. High-density diffuse optical tomography (HD-DOT) provides high-fidelity mapping of human brain function with comparable spatial resolution to that of fMRI but in a silent and open scanning environment similar to real-life social scenarios. Therefore, HD-DOT has potential to be used in naturalistic settings where other neuroimaging modalities are limited. While HD-DOT has been previously validated against fMRI for mapping the neural correlates underlying language comprehension and covert (i.e., "silent") language production, HD-DOT has not yet been established for mapping the cortical responses to overt (i.e., "out loud") language production. In this study, we assessed the brain regions supporting a simple hierarchy of language tasks: silent reading of single words, covert production of verbs, and overt production of verbs in normal hearing right-handed native English speakers (n = 33). First, we found that HD-DOT brain mapping is resilient to movement associated with overt speaking. Second, we observed that HD-DOT is sensitive to key activations and deactivations in brain function underlying the perception and naturalistic production of language. Specifically, statistically significant results were observed that show recruitment of regions in occipital, temporal, motor, and prefrontal cortices across all three tasks after performing stringent cluster-extent based thresholding. Our findings lay the foundation for future HD-DOT studies of imaging naturalistic language comprehension and production during real-life social interactions and for broader applications such as presurgical language assessment and brain-machine interfaces.

Bimodal electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition

The recognition of inner speech, which could give a 'voice' to patients that have no ability to speak or move, is a challenge for brain-computer interfaces (BCIs). A shortcoming of the available datasets is that they do not combine modalities to increase the performance of inner speech recognition. Multimodal datasets of brain data enable the fusion of neuroimaging modalities with complimentary properties, such as the high spatial resolution of functional magnetic resonance imaging (fMRI) and the temporal resolution of electroencephalography (EEG), and therefore are promising for decoding inner speech. This paper presents the first publicly available bimodal dataset containing EEG and fMRI data acquired nonsimultaneously during inner-speech production. Data were obtained from four healthy, right-handed participants during an inner-speech task with words in either a social or numerical category. Each of the 8-word stimuli were assessed with 40 trials, resulting in 320 trials in each modality for each participant. The aim of this work is to provide a publicly available bimodal dataset on inner speech, contributing towards speech prostheses.

Neural representations of the content and production of human vocalization

Speech, as the spoken form of language, is fundamental for human communication. The phenomenon of covert inner speech implies functional independence of speech content and motor production. However, it remains unclear how a flexible mapping between speech content and production is achieved on the neural level. To address this, we recorded magnetoencephalography in humans performing a rule-based vocalization task. On each trial, vocalization content (one of two vowels) and production form (overt or covert) were instructed independently. Using multivariate pattern analysis, we found robust neural information about vocalization content and production, mostly originating from speech areas of the left hemisphere. Production signals dynamically transformed upon presentation of the content cue, whereas content signals remained largely stable throughout the trial. In sum, our results show dissociable neural representations of vocalization content and production in the human brain and provide insights into the neural dynamics underlying human vocalization.

The nested hierarchy of overt, mouthed, and imagined speech activity evident in intracranial recordings

Recent studies have demonstrated that it is possible to decode and synthesize various aspects of acoustic speech directly from intracranial measurements of electrophysiological brain activity. In order to continue progressing toward the development of a practical speech neuroprosthesis for the individuals with speech impairments, better understanding and modeling of imagined speech processes are required. The present study uses intracranial brain recordings from participants that performed a speaking task with trials consisting of overt, mouthed, and imagined speech modes, representing various degrees of decreasing behavioral output. Speech activity detection models are constructed using spatial, spectral, and temporal brain activity features, and the features and model performances are characterized and compared across the three degrees of behavioral output. The results indicate the existence of a hierarchy in which the relevant channels for the lower behavioral output modes form nested subsets of the relevant channels from the higher behavioral output modes. This provides important insights for the elusive goal of developing more effective imagined speech decoding models with respect to the better-established overt speech decoding counterparts.

Duration of oral contraceptive use relates to cognitive performance and brain activation in current and past users

Previous studies indicate effects of oral contraceptive (OC) use on spatial and verbal cognition. However, a better understanding of the OC effects is still needed, including the differential effects of androgenic or anti-androgenic OC use and whether the possible impact persists beyond the OC use. We aim to investigate the associations of OC use duration with spatial and verbal cognition, differentiating between androgenic and anti-androgenic OC. Using functional magnetic resonance imaging (MRI), we scanned a group of 94 past and current OC-users in a single session. We grouped current OC users (N=53) and past OC users with a natural cycle (N=41) into androgenic and anti-androgenic user. Effects of OC use duration were observed for current use and after discontinuation. Duration of OC use was reflected only in verbal fluency performance but not navigation: The longer the current OC use, the less words were produced in the verbal fluency task. During navigation, deactivation in the caudate and postcentral gyrus was duration-dependent in current androgenic OC users. Only during the verbal fluency task, duration of previous OC use affects several brain parameters, including activation of the left putamen and connectivity between right-hemispheric language areas (i.e., right inferior frontal gyrus and right angular gyrus). The results regarding performance and brain activation point towards stronger organizational effects of OCs on verbal rather than spatial processing. Irrespective of the task, a duration-dependent connectivity between the hippocampus and various occipital areas was observed. This could suggest a shift in strategy or processing style with long-term contraceptive use during navigation/verbal fluency. The current findings suggest a key role of the progestogenic component of OCs in both tasks. The influence of OC use on verbal fluency remains even after discontinuation which further points out the importance of future studies on OC effects and their reversibility.

Overt speech critically changes lateralization index and did not allow determination of hemispheric dominance for language: an fMRI study

Background

Pre-surgical mapping of language using functional MRI aimed principally to determine the dominant hemisphere. This mapping is currently performed using covert linguistic task in way to avoid motion artefacts potentially biasing the results. However, overt task is closer to natural speaking, allows a control on the performance of the task, and may be easier to perform for stressed patients and children. However, overt task, by activating phonological areas on both hemispheres and areas involved in pitch prosody control in the non-dominant hemisphere, is expected to modify the determination of the dominant hemisphere by the calculation of the lateralization index (LI).

Objective

Here, we analyzed the modifications in the LI and the interactions between cognitive networks during covert and overt speech task.

Methods

Thirty-three volunteers participated in this study, all but four were right-handed. They performed three functional sessions consisting of (1) covert and (2) overt generation of a short sentence semantically linked with an audibly presented word, from which we estimated the “Covert” and “Overt” contrasts, and a (3) resting-state session. The resting-state session was submitted to spatial independent component analysis to identify language network at rest (LANG), cingulo-opercular network (CO), and ventral attention network (VAN). The LI was calculated using the bootstrapping method.

Results

The LI of the LANG was the most left-lateralized (0.66 ± 0.38). The LI shifted from a moderate leftward lateralization for the Covert contrast (0.32 ± 0.38) to a right lateralization for the Overt contrast (− 0.13 ± 0.30). The LI significantly differed from each other. This rightward shift was due to the recruitment of right hemispheric temporal areas together with the nodes of the CO.

Conclusion

Analyzing the overt speech by fMRI allowed improvement in the physiological knowledge regarding the coordinated activity of the intrinsic connectivity networks. However, the rightward shift of the LI in this condition did not provide the basic information on the hemispheric language dominance. Overt linguistic task cannot be recommended for clinical purpose when determining hemispheric dominance for language.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12868-021-00671-y.

Decoding Covert Speech From EEG-A Comprehensive Review

Over the past decade, many researchers have come up with different implementations of systems for decoding covert or imagined speech from EEG (electroencephalogram). They differ from each other in several aspects, from data acquisition to machine learning algorithms, due to which, a comparison between different implementations is often difficult. This review article puts together all the relevant works published in the last decade on decoding imagined speech from EEG into a single framework. Every important aspect of designing such a system, such as selection of words to be imagined, number of electrodes to be recorded, temporal and spatial filtering, feature extraction and classifier are reviewed. This helps a researcher to compare the relative merits and demerits of the different approaches and choose the one that is most optimal. Speech being the most natural form of communication which human beings acquire even without formal education, imagined speech is an ideal choice of prompt for evoking brain activity patterns for a BCI (brain-computer interface) system, although the research on developing real-time (online) speech imagery based BCI systems is still in its infancy. Covert speech based BCI can help people with disabilities to improve their quality of life. It can also be used for covert communication in environments that do not support vocal communication. This paper also discusses some future directions, which will aid the deployment of speech imagery based BCI for practical applications, rather than only for laboratory experiments.

Overt speech feasibility using continuous functional magnetic resonance imaging: Isolation of areas involved in phonology and prosody

To avoid motion artifacts, almost all speech-related functional magnetic resonance imagings (fMRIs) are performed covertly to detect language activations. This method may be difficult to execute, especially by patients with brain tumors, and does not allow the identification of phonological areas. Here, we aimed to evaluate overt task feasibility. Thirty-three volunteers participated in this study. They performed two functional sessions of covert and overt generation of a short sentence semantically linked with a word. Three main contrasts were performed: Covert and Overt for the isolation of language-activated areas, and Overt > Covert for the isolation of the motor cortical activation of speech. fMRI data preprocessing was performed with and without unwarping, and with and without regression of movement parameters as confounding variables. All types of results were compared to each other. For the Overt contrast, Dice coefficients showed strong overlap between each pair of types of results: 0.98 for the pair with and without unwarping, and 0.9 for the pair with and without movement parameter regression. The Overt > Covert contrast allowed isolation of motor laryngeal activations with high statistical reliability and revealed the right-lateralized temporal activity related to acoustic feedback. Overt speaking during magnetic resonance imaging induced few artifacts and did not significantly affect the results, allowing the identification of areas involved in primary motor control and prosodic regulation of speech. Unwarping and motion artifact regression in the postprocessing step, seem to not be necessary. Changes in lateralization of cortical activity by overt speech shall be explored before using these tasks for presurgical mapping.

Mapping typical and hypokinetic dysarthric speech production network using a connected speech paradigm in functional MRI

We developed a task paradigm whereby subjects spoke aloud while minimizing head motion during functional MRI (fMRI) in order to better understand the neural circuitry involved in motor speech disorders due to dysfunction of the central nervous system. To validate our overt continuous speech paradigm, we mapped the speech production network (SPN) in typical speakers (n = 19, 10 females) and speakers with hypokinetic dysarthria as a manifestation of Parkinson disease (HKD; n = 21, 8 females) in fMRI. We then compared it with the SPN derived during overt speech production by ¹⁵O-water PET in the same group of typical speakers and another HKD cohort (n = 10, 2 females). The fMRI overt connected speech paradigm did not result in excessive motion artifacts and successfully identified the same brain areas demonstrated in the PET studies in the two cohorts. The SPN derived in fMRI demonstrated significant spatial overlap with the corresponding PET derived maps (typical speakers: r = 0.52; speakers with HKD: r = 0.43) and identified the components of the neural circuit of speech production belonging to the feedforward and feedback subsystems. The fMRI study in speakers with HKD identified significantly decreased activity in critical feedforward (bilateral dorsal premotor and motor cortices) and feedback (auditory and somatosensory areas) subsystems replicating previous PET study findings in this cohort. These results demonstrate that the overt connected speech paradigm is feasible during fMRI and can accurately localize the neural substrates of typical and disordered speech production. Our fMRI paradigm should prove useful for study of motor speech and voice disorders, including stuttering, apraxia of speech, dysarthria, and spasmodic dysphonia.

Decoding Imagined and Spoken Phrases From Non-invasive Neural (MEG) Signals

Speech production is a hierarchical mechanism involving the synchronization of the brain and the oral articulators, where the intention of linguistic concepts is transformed into meaningful sounds. Individuals with locked-in syndrome (fully paralyzed but aware) lose their motor ability completely including articulation and even eyeball movement. The neural pathway may be the only option to resume a certain level of communication for these patients. Current brain-computer interfaces (BCIs) use patients' visual and attentional correlates to build communication, resulting in a slow communication rate (a few words per minute). Direct decoding of imagined speech from the neural signals (and then driving a speech synthesizer) has the potential for a higher communication rate. In this study, we investigated the decoding of five imagined and spoken phrases from single-trial, non-invasive magnetoencephalography (MEG) signals collected from eight adult subjects. Two machine learning algorithms were used. One was an artificial neural network (ANN) with statistical features as the baseline approach. The other was convolutional neural networks (CNNs) applied on the spatial, spectral and temporal features extracted from the MEG signals. Experimental results indicated the possibility to decode imagined and spoken phrases directly from neuromagnetic signals. CNNs were found to be highly effective with an average decoding accuracy of up to 93% for the imagined and 96% for the spoken phrases.

The Brain Differentially Prepares Inner and Overt Speech Production: Electrophysiological and Vascular Evidence

Speech production not only relies on spoken (overt speech) but also on silent output (inner speech). Little is known about whether inner and overt speech are processed differently and which neural mechanisms are involved. By simultaneously applying electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), we tried to disentangle executive control from motor and linguistic processes. A preparation phase was introduced additionally to the examination of overt and inner speech directly during naming (i.e., speech execution). Participants completed a picture-naming paradigm in which the pure preparation phase of a subsequent speech production and the actual speech execution phase could be differentiated. fNIRS results revealed a larger activation for overt rather than inner speech at bilateral prefrontal to parietal regions during the preparation and at bilateral temporal regions during the execution phase. EEG results showed a larger negativity for inner compared to overt speech between 200 and 500 ms during the preparation phase and between 300 and 500 ms during the execution phase. Findings of the preparation phase indicated that differences between inner and overt speech are not exclusively driven by specific linguistic and motor processes but also impacted by inhibitory mechanisms. Results of the execution phase suggest that inhibitory processes operate during phonological code retrieval and encoding.

Examining the neural and cognitive processes that underlie reading through naming speed tasks

We combined fMRI with eye tracking and speech recording to examine the neural and cognitive mechanisms that underlie reading. To simplify the study of the complex processes involved during reading, we used naming speed (NS) tasks (also known as rapid automatized naming or RAN) as a focus for this study, in which average reading right-handed adults named sets of stimuli (letters or objects) as quickly and accurately as possible. Due to the possibility of spoken output during fMRI studies creating motion artifacts, we employed both an overt session and a covert session. When comparing the two sessions, there were no significant differences in behavioral performance, sensorimotor activation (except for regions involved in the motor aspects of speech production) or activation in regions within the left-hemisphere-dominant neural reading network. This established that differences found between the tasks within the reading network were not attributed to speech production motion artifacts or sensorimotor processes. Both behavioral and neuroimaging measures showed that letter naming was a more automatic and efficient task than object naming. Furthermore, specific manipulations to the NS tasks to make the stimuli more visually and/or phonologically similar differentially activated the reading network in the left hemisphere associated with phonological, orthographic and orthographic-to-phonological processing, but not articulatory/motor processing related to speech production. These findings further our understanding of the underlying neural processes that support reading by examining how activation within the reading network differs with both task performance and task characteristics.

The ConDialInt Model: Condensation, Dialogality, and Intentionality Dimensions of Inner Speech Within a Hierarchical Predictive Control Framework

Inner speech has been shown to vary in form along several dimensions. Along condensation, condensed inner speech forms have been described, that are supposed to be deprived of acoustic, phonological and even syntactic qualities. Expanded forms, on the other extreme, display articulatory and auditory properties. Along dialogality, inner speech can be monologal, when we engage in internal soliloquy, or dialogal, when we recall past conversations or imagine future dialogs involving our own voice as well as that of others addressing us. Along intentionality, it can be intentional (when we deliberately rehearse material in short-term memory) or it can arise unintentionally (during mind wandering). We introduce the ConDialInt model, a neurocognitive predictive control model of inner speech that accounts for its varieties along these three dimensions. ConDialInt spells out the condensation dimension by including inhibitory control at the conceptualization, formulation or articulatory planning stage. It accounts for dialogality, by assuming internal model adaptations and by speculating on neural processes underlying perspective switching. It explains the differences between intentional and spontaneous varieties in terms of monitoring. We present an fMRI study in which we probed varieties of inner speech along dialogality and intentionality, to examine the validity of the neuroanatomical correlates posited in ConDialInt. Condensation was also informally tackled. Our data support the hypothesis that expanded inner speech recruits speech production processes down to articulatory planning, resulting in a predicted signal, the inner voice, with auditory qualities. Along dialogality, covertly using an avatar's voice resulted in the activation of right hemisphere homologs of the regions involved in internal own-voice soliloquy and in reduced cerebellar activation, consistent with internal model adaptation. Switching from first-person to third-person perspective resulted in activations in precuneus and parietal lobules. Along intentionality, compared with intentional inner speech, mind wandering with inner speech episodes was associated with greater bilateral inferior frontal activation and decreased activation in left temporal regions. This is consistent with the reported subjective evanescence and presumably reflects condensation processes. Our results provide neuroanatomical evidence compatible with predictive control and in favor of the assumptions made in the ConDialInt model.

Neural Correlates of Music Listening and Recall in the Human Brain

Previous neuroimaging studies have identified various brain regions that are activated by music listening or recall. However, little is known about how these brain regions represent the time course and temporal features of music during listening and recall. Here we analyzed neural activity in different brain regions associated with music listening and recall using electrocorticography recordings obtained from 10 epilepsy patients of both genders implanted with subdural electrodes. Electrocorticography signals were recorded while subjects were listening to familiar instrumental music or recalling the same music pieces by imagery. During the onset phase (0-500 ms), music listening initiated cortical activity in high-gamma band in the temporal lobe and supramarginal gyrus, followed by the precentral gyrus and the inferior frontal gyrus. In contrast, during music recall, the high-gamma band activity first appeared in the inferior frontal gyrus and precentral gyrus, and then spread to the temporal lobe, showing a reversed temporal sequential order. During the sustained phase (after 500 ms), delta band and high-gamma band responses in the supramarginal gyrus, temporal and frontal lobes dynamically tracked the intensity envelope of the music during listening or recall with distinct temporal delays. During music listening, the neural tracking by the frontal lobe lagged behind that of the temporal lobe; whereas during music recall, the neural tracking by the frontal lobe preceded that of the temporal lobe. These findings demonstrate bottom-up and top-down processes in the cerebral cortex during music listening and recall and provide important insights into music processing by the human brain.SIGNIFICANCE STATEMENT Understanding how the brain analyzes, stores, and retrieves music remains one of the most challenging problems in neuroscience. By analyzing direct neural recordings obtained from the human brain, we observed dispersed and overlapping brain regions associated with music listening and recall. Music listening initiated cortical activity in high-gamma band starting from the temporal lobe and ending at the inferior frontal gyrus. A reversed temporal flow was observed in high-gamma response during music recall. Neural responses of frontal and temporal lobes dynamically tracked the intensity envelope of music that was presented or imagined during listening or recall. These findings demonstrate bottom-up and top-down processes in the cerebral cortex during music listening and recall.

The use of intracranial recordings to decode human language: Challenges and opportunities

Decoding speech from intracranial recordings serves two main purposes: understanding the neural correlates of speech processing and decoding speech features for targeting speech neuroprosthetic devices. Intracranial recordings have high spatial and temporal resolution, and thus offer a unique opportunity to investigate and decode the electrophysiological dynamics underlying speech processing. In this review article, we describe current approaches to decoding different features of speech perception and production - such as spectrotemporal, phonetic, phonotactic, semantic, and articulatory components - using intracranial recordings. A specific section is devoted to the decoding of imagined speech, and potential applications to speech prosthetic devices. We outline the challenges in decoding human language, as well as the opportunities in scientific and neuroengineering applications.

Neurolinguistics Research Advancing Development of a Direct-Speech Brain-Computer Interface

A direct-speech brain-computer interface (DS-BCI) acquires neural signals corresponding to imagined speech, then processes and decodes these signals to produce a linguistic output in the form of phonemes, words, or sentences. Recent research has shown the potential of neurolinguistics to enhance decoding approaches to imagined speech with the inclusion of semantics and phonology in experimental procedures. As neurolinguistics research findings are beginning to be incorporated within the scope of DS-BCI research, it is our view that a thorough understanding of imagined speech, and its relationship with overt speech, must be considered an integral feature of research in this field. With a focus on imagined speech, we provide a review of the most important neurolinguistics research informing the field of DS-BCI and suggest how this research may be utilized to improve current experimental protocols and decoding techniques. Our review of the literature supports a cross-disciplinary approach to DS-BCI research, in which neurolinguistics concepts and methods are utilized to aid development of a naturalistic mode of communication.

Contralateral functional reorganization of the speech supplementary motor area following neurosurgical tumor resection

We evaluated plasticity in speech supplemental motor area (SMA) tissue in two patients using functional magnetic resonance imaging (fMRI), following resection of tumors in or associated with the dominant hemisphere speech SMA. Patient A underwent resection of a anaplastic astrocytoma NOS associated with the left speech SMA, experienced SMA syndrome related mutism postoperatively, but experienced full recovery 14 months later. FMRI performed 32 months after surgery demonstrated a migration of speech SMA to homologous contralateral hemispheric regional tissue. Patient B underwent resection of a oligodendroglioma NOS in the left speech SMA, and postoperatively experienced speech hesitancy, latency and poor fluency, which gradually resolved over 18 months. FMRI performed at 64 months after surgery showed a reorganization of speech SMA to the contralateral hemisphere. These data support the hypothesis of dynamic, time based plasticity in speech SMA tissue, and may represent a noninvasive neural marker for SMA syndrome recovery.

Decoding Inner Speech Using Electrocorticography: Progress and Challenges Toward a Speech Prosthesis

Certain brain disorders resulting from brainstem infarcts, traumatic brain injury, cerebral palsy, stroke, and amyotrophic lateral sclerosis, limit verbal communication despite the patient being fully aware. People that cannot communicate due to neurological disorders would benefit from a system that can infer internal speech directly from brain signals. In this review article, we describe the state of the art in decoding inner speech, ranging from early acoustic sound features, to higher order speech units. We focused on intracranial recordings, as this technique allows monitoring brain activity with high spatial, temporal, and spectral resolution, and therefore is a good candidate to investigate inner speech. Despite intense efforts, investigating how the human cortex encodes inner speech remains an elusive challenge, due to the lack of behavioral and observable measures. We emphasize various challenges commonly encountered when investigating inner speech decoding, and propose potential solutions in order to get closer to a natural speech assistive device.

The Effect of Speech Repetition Rate on Neural Activation in Healthy Adults: Implications for Treatment of Aphasia and Other Fluency Disorders

Functional imaging studies have provided insight into the effect of rate on production of syllables, pseudowords, and naturalistic speech, but the influence of rate on repetition of commonly-used words/phrases suitable for therapeutic use merits closer examination. Aim: To identify speech-motor regions responsive to rate and test the hypothesis that those regions would provide greater support as rates increase, we used an overt speech repetition task and functional magnetic resonance imaging (fMRI) to capture rate-modulated activation within speech-motor regions and determine whether modulations occur linearly and/or show hemispheric preference. Methods: Twelve healthy, right-handed adults participated in an fMRI task requiring overt repetition of commonly-used words/phrases at rates of 1, 2, and 3 syllables/second (syll./sec.). Results: Across all rates, bilateral activation was found both in ventral portions of primary sensorimotor cortex and middle and superior temporal regions. A repeated measures analysis of variance with pairwise comparisons revealed an overall difference between rates in temporal lobe regions of interest (ROIs) bilaterally (p < 0.001); all six comparisons reached significance (p < 0.05). Five of the six were highly significant (p < 0.008), while the left-hemisphere 2- vs. 3-syll./sec. comparison, though still significant, was less robust (p = 0.037). Temporal ROI mean beta-values increased linearly across the three rates bilaterally. Significant rate effects observed in the temporal lobes were slightly more pronounced in the right-hemisphere. No significant overall rate differences were seen in sensorimotor ROIs, nor was there a clear hemispheric effect. Conclusion: Linear effects in superior temporal ROIs suggest that sensory feedback corresponds directly to task demands. The lesser degree of significance in left-hemisphere activation at the faster, closer-to-normal rate may represent an increase in neural efficiency (and therefore, decreased demand) when the task so closely approximates a highly-practiced function. The presence of significant bilateral activation during overt repetition of words/phrases at all three rates suggests that repetition-based speech production may draw support from either or both hemispheres. This bihemispheric redundancy in regions associated with speech-motor control and their sensitivity to changes in rate may play an important role in interventions for nonfluent aphasia and other fluency disorders, particularly when right-hemisphere structures are the sole remaining pathway for production of meaningful speech.

Neurophysiological evidence of efference copies to inner speech

Efference copies refer to internal duplicates of movement-producing neural signals. Their primary function is to predict, and often suppress, the sensory consequences of willed movements. Efference copies have been almost exclusively investigated in the context of overt movements. The current electrophysiological study employed a novel design to show that inner speech – the silent production of words in one’s mind – is also associated with an efference copy. Participants produced an inner phoneme at a precisely specified time, at which an audible phoneme was concurrently presented. The production of the inner phoneme resulted in electrophysiological suppression, but only if the content of the inner phoneme matched the content of the audible phoneme. These results demonstrate that inner speech – a purely mental action – is associated with an efference copy with detailed auditory properties. These findings suggest that inner speech may ultimately reflect a special type of overt speech.

As you read this text, the chances are you can hear your own inner voice narrating the words. You may hear your inner voice again when silently considering what to have for lunch, or imagining how a phone conversation this afternoon will play out. Estimates suggest that we spend at least a quarter of our lives listening to our own inner speech. But to what extent does the brain distinguish between inner speech and the sounds we produce when we speak out loud?

Listening to a recording of your own voice activates the brain more than hearing yourself speak out loud. This is because when the brain sends instructions to the lips, tongue, and vocal cords telling them to move, it also makes a copy of these instructions. This is known as an efference copy, and it enables regions of the brain that process sounds to predict what they are about to hear. When the actual sounds match those predicted – as when you hear yourself speak out loud – the brain’s sound-processing regions dampen down their responses.

But does the inner speech in our heads also generate an efference copy? To find out, Whitford et al. tracked the brain activity of healthy volunteers as they listened to speech sounds through headphones. While listening to the sounds, the volunteers had to produce either the same speech sound or a different speech sound inside their heads. A specific type of brain activity decreased whenever the inner speech sound matched the external speech sound. This decrease did not occur when the two sounds were different. This suggests that the brain produces an efference copy for inner speech similar to that for external speech.

These findings could ultimately benefit people who suffer from psychotic symptoms, for example as part of schizophrenia. Symptoms such as hearing voices are thought to reflect problems with producing and interpreting inner speech. The technique that Whitford et al. have developed will enable us to test this long-held but hitherto untestable idea. The results should increase our understanding of these symptoms and may eventually lead to new treatments.

Key considerations in designing a speech brain-computer interface

Restoring communication in case of aphasia is a key challenge for neurotechnologies. To this end, brain-computer strategies can be envisioned to allow artificial speech synthesis from the continuous decoding of neural signals underlying speech imagination. Such speech brain-computer interfaces do not exist yet and their design should consider three key choices that need to be made: the choice of appropriate brain regions to record neural activity from, the choice of an appropriate recording technique, and the choice of a neural decoding scheme in association with an appropriate speech synthesis method. These key considerations are discussed here in light of (1) the current understanding of the functional neuroanatomy of cortical areas underlying overt and covert speech production, (2) the available literature making use of a variety of brain recording techniques to better characterize and address the challenge of decoding cortical speech signals, and (3) the different speech synthesis approaches that can be considered depending on the level of speech representation (phonetic, acoustic or articulatory) envisioned to be decoded at the core of a speech BCI paradigm.

Orofacial electromyographic correlates of induced verbal rumination

Rumination is predominantly experienced in the form of repetitive verbal thoughts. Verbal rumination is a particular case of inner speech. According to the Motor Simulation view, inner speech is a kind of motor action, recruiting the speech motor system. In this framework, we predicted an increase in speech muscle activity during rumination as compared to rest. We also predicted increased forehead activity, associated with anxiety during rumination. We measured electromyographic activity over the orbicularis oris superior and inferior, frontalis and flexor carpi radialis muscles. Results showed increased lip and forehead activity after rumination induction compared to an initial relaxed state, together with increased self-reported levels of rumination. Moreover, our data suggest that orofacial relaxation is more effective in reducing rumination than non-orofacial relaxation. Altogether, these results support the hypothesis that verbal rumination involves the speech motor system, and provide a promising psychophysiological index to assess the presence of verbal rumination.

Left posterior-dorsal area 44 couples with parietal areas to promote speech fluency, while right area 44 activity promotes the stopping of motor responses

Area 44 is a cytoarchitectonically distinct portion of Broca's region. Parallel and overlapping large-scale networks couple with this region thereby orchestrating heterogeneous language, cognitive, and motor functions. In the context of stuttering, area 44 frequently comes into focus because structural and physiological irregularities affect developmental trajectories, stuttering severity, persistency, and etiology. A remarkable phenomenon accompanying stuttering is the preserved ability to sing. Speaking and singing are connatural behaviours recruiting largely overlapping brain networks including left and right area 44. Analysing which potential subregions of area 44 are malfunctioning in adults who stutter, and what effectively suppresses stuttering during singing, may provide a better understanding of the coordination and reorganization of large-scale brain networks dedicated to speaking and singing in general. We used fMRI to investigate functionally distinct subregions of area 44 during imagery of speaking and imaginary of humming a melody in 15 dextral males who stutter and 17 matched control participants. Our results are fourfold. First, stuttering was specifically linked to a reduced activation of left posterior-dorsal area 44, a subregion that is involved in speech production, including phonological word processing, pitch processing, working memory processes, sequencing, motor planning, pseudoword learning, and action inhibition. Second, functional coupling between left posterior area 44 and left inferior parietal lobule was deficient in stuttering. Third, despite the preserved ability to sing, males who stutter showed bilaterally a reduced activation of area 44 when imagine humming a melody, suggesting that this fluency-enhancing condition seems to bypass posterior-dorsal area 44 to achieve fluency. Fourth, time courses of the posterior subregions in area 44 showed delayed peak activations in the right hemisphere in both groups, possibly signaling the offset response. Because these offset response-related activations in the right hemisphere were comparably large in males who stutter, our data suggest a hyperactive mechanism to stop speech motor responses and thus possibly reflect a pathomechanism, which, until now, has been neglected. Overall, the current results confirmed a recently described co-activation based parcellation supporting the idea of functionally distinct subregions of left area 44.

Modulation of Orthographic Decoding by Frontal Cortex

Opinions are divided on whether word reading processes occur in a hierarchical, feedforward fashion or within an interactive framework. To critically evaluate these competing theories, we recorded electrocorticographic (ECoG) data from 15 human patients with intractable epilepsy during a word completion task and evaluated brain network dynamics across individuals. We used a novel technique of analyzing multihuman ECoG recordings to identify cortical regions most relevant to processing lexical information. The mid fusiform gyrus showed the strongest, earliest response after stimulus onset, whereas activity was maximal in frontal, dorsal lateral prefrontal, and sensorimotor regions toward articulation onset. To evaluate interregional functional connectivity, ECoG data from electrodes situated over specific cortical regions of interest were fit into linear multivariate autoregressive (MVAR) models. Spectral characteristics of the MVAR models were used to precisely reveal the timing and the magnitude of information flow between localized brain regions. This is the first application of MVAR for developing a comprehensive account of interregional interactions from a word reading ECoG dataset. Our comprehensive findings revealed both top-down and bottom-up influences between higher-level language areas and the mid fusiform gyrus. Our findings thus challenge strictly hierarchical, feedforward views of word reading and suggest that orthographic processes are modulated by prefrontal and sensorimotor regions via an interactive framework.

SIGNIFICANCE STATEMENT

Word reading is a critical part of everyday life. When the ability to read is disrupted, it can lead to learning disorders, as well as emotional and academic difficulties. The neural mechanisms underlying word reading are not well understood due to limitations in the spatial and temporal specificity of prior word reading studies. Our research analyzed data recorded from sensors implanted directly from surface of human brains while these individuals performed a word reading task. Our research analyzed these recordings to infer how brain regions communicate during word reading. Our original results improve upon current models of word reading and can be used to develop treatment plans for individuals with reading disabilities.

Word pair classification during imagined speech using direct brain recordings

People that cannot communicate due to neurological disorders would benefit from an internal speech decoder. Here, we showed the ability to classify individual words during imagined speech from electrocorticographic signals. In a word imagery task, we used high gamma (70–150 Hz) time features with a support vector machine model to classify individual words from a pair of words. To account for temporal irregularities during speech production, we introduced a non-linear time alignment into the SVM kernel. Classification accuracy reached 88% in a two-class classification framework (50% chance level), and average classification accuracy across fifteen word-pairs was significant across five subjects (mean = 58%; p < 0.05). We also compared classification accuracy between imagined speech, overt speech and listening. As predicted, higher classification accuracy was obtained in the listening and overt speech conditions (mean = 89% and 86%, respectively; p < 0.0001), where speech stimuli were directly presented. The results provide evidence for a neural representation for imagined words in the temporal lobe, frontal lobe and sensorimotor cortex, consistent with previous findings in speech perception and production. These data represent a proof of concept study for basic decoding of speech imagery, and delineate a number of key challenges to usage of speech imagery neural representations for clinical applications.

Development of neural basis for chinese orthographic neighborhood size effect

The brain activity of orthographic neighborhood size (N size) effect in Chinese character naming has been studied in adults, meanwhile behavioral studies have revealed a developmental trend of Chinese N-size effect in developing readers. However, it is unclear whether and how the neural mechanism of N-size effect changes in Chinese children along with development. Here we address this issue using functional magnetic resonance imaging. Forty-four students from the 3(rd) , 5(th) , and 7(th) grades were scanned during silent naming of Chinese characters. After scanning, all participants took part in an overt naming test outside the scanner, and results of the naming task showed that the 3(rd) graders named characters from large neighborhoods faster than those from small neighborhoods, revealing a facilitatory N-size effect; the 5(th) graders showed null N-size effect while the 7(th) graders showed an inhibitory N-size effect. Neuroimaging results revealed that only the 3(rd) graders exhibited a significant N-size effect in the left middle occipital activity, with greater activation for large N-size characters. Results of 5(th) and 7(th) graders showed significant N-size effects in the left middle frontal gyrus, in which 5(th) graders induced greater activation in large N-size condition than in small N-size condition, while 7(th) graders exhibited an opposite effect which was similar to the adult pattern reported in a previous study. The current findings suggested the transition from broadly tuned to finely tuned orthographic representation with reading development, and the inhibition from neighbors' phonology for higher graders. Hum Brain Mapp 37:632-647, 2016. © 2015 Wiley Periodicals, Inc.

Mental imagery of speech implicates two mechanisms of perceptual reactivation

Sensory cortices can be activated without any external stimuli. Yet, it is still unclear how this perceptual reactivation occurs and which neural structures mediate this reconstruction process. In this study, we employed fMRI with mental imagery paradigms to investigate the neural networks involved in perceptual reactivation. Subjects performed two speech imagery tasks: articulation imagery (AI) and hearing imagery (HI). We found that AI induced greater activity in frontal-parietal sensorimotor systems, including sensorimotor cortex, subcentral (BA 43), middle frontal cortex (BA 46) and parietal operculum (PO), whereas HI showed stronger activation in regions that have been implicated in memory retrieval: middle frontal (BA 8), inferior parietal cortex and intraparietal sulcus. Moreover, posterior superior temporal sulcus (pSTS) and anterior superior temporal gyrus (aSTG) was activated more in AI compared with HI, suggesting that covert motor processes induced stronger perceptual reactivation in the auditory cortices. These results suggest that motor-to-perceptual transformation and memory retrieval act as two complementary mechanisms to internally reconstruct corresponding perceptual outcomes. These two mechanisms can serve as a neurocomputational foundation for predicting perceptual changes, either via a previously learned relationship between actions and their perceptual consequences or via stored perceptual experiences of stimulus and episodic or contextual regularity.

Preoperative functional MRI localization of language areas in Chinese patients with brain tumors: Validation with intraoperative electrocortical mapping

Ten Chinese patients with brain tumors involving language regions were selected. Preoperative functional MRI was performed to locate Broca's or Wernicke's area, and the cortex that was essential for language function was determined by electrocortical mapping. A site-by-site comparison between functional MRI and electrocortical mapping was performed with the aid of a neuronavigation device. Results showed that the sensitivity and specificity of preoperative functional MRI were 80.0% and 85.0% in Broca's area and 66.6% and 85.2% in Wernicke's area, respectively. These experimental findings indicate that functional MRI is an accurate, reliable technique with which to identify the location of Wernicke's area or Broca's area in patients with brain tumors.

Language and visual perception associations: meta-analytic connectivity modeling of Brodmann area 37

BACKGROUND

Understanding the functions of different brain areas has represented a major endeavor of neurosciences. Historically, brain functions have been associated with specific cortical brain areas; however, modern neuroimaging developments suggest cognitive functions are associated to networks rather than to areas.

OBJECTIVE

The purpose of this paper was to analyze the connectivity of Brodmann area (BA) 37 (posterior, inferior, and temporal/fusiform gyrus) in relation to (1) language and (2) visual processing.

METHODS

Two meta-analyses were initially conducted (first level analysis). The first one was intended to assess the language network in which BA37 is involved. The second one was intended to assess the visual perception network. A third meta-analysis (second level analysis) was then performed to assess contrasts and convergence between the two cognitive domains (language and visual perception). The DataBase of Brainmap was used.

RESULTS

Our results support the role of BA37 in language but by means of a distinct network from the network that supports its second most important function: visual perception.

CONCLUSION

It was concluded that left BA37 is a common node of two distinct networks-visual recognition (perception) and semantic language functions.

Associations between private speech, behavioral self-regulation, and cognitive abilities

We examined the associations between 5-year-old children’s private speech, behavioural self-regulation, and cognitive abilities. Behavioural self-regulation was assessed using parental and preschool teacher questionnaires. Cognitive abilities (i.e., language, inhibition, planning and fluency, and memory) were assessed with neurocognitive tests, and the effectiveness of private speech (i.e., whether the child performs better when using speech than when not using speech) with the Hammer Task. About 43% of the children used private speech spontaneously, and about 76% performed better on the Hammer Task when they used speech. Associations between behavioural self-regulation and speech effectiveness were few, but all cognitive scores were significantly associated with the speech effectiveness score, i.e., the poorer the child’s neurocognitive test performance was, the more he/she benefited from using speech. The findings lend support to the relevance of children’s cognitive abilities when seeking understanding on the development, use, and effectiveness of private speech.

Task dependent lexicality effects support interactive models of reading: a meta-analytic neuroimaging review

Models of reading must explain how orthographic input activates a phonological representation, and elicits the retrieval of word meaning from semantic memory. Comparisons between tasks that theoretically differ with respect to the degree to which they rely on connections between orthographic, phonological and semantic systems during reading can thus provide valuable insight into models of reading, but such direct comparisons are not well-represented in the literature. An ALE meta-analysis explored lexicality effects directly contrasting words and pseudowords using the lexical decision task and overt or covert naming, which we assume rely most on the semantic and phonological systems, respectively. Interactions between task and lexicality effects demonstrate that different demands of the lexical decision and naming tasks lead to different manifestations of lexicality effects.

Sensory-motor integration during speech production localizes to both left and right plana temporale

Speech production relies on fine voluntary motor control of respiration, phonation, and articulation. The cortical initiation of complex sequences of coordinated movements is thought to result in parallel outputs, one directed toward motor neurons while the "efference copy" projects to auditory and somatosensory fields. It is proposed that the latter encodes the expected sensory consequences of speech and compares expected with actual postarticulatory sensory feedback. Previous functional neuroimaging evidence has indicated that the cortical target for the merging of feedforward motor and feedback sensory signals is left-lateralized and lies at the junction of the supratemporal plane with the parietal operculum, located mainly in the posterior half of the planum temporale (PT). The design of these studies required participants to imagine speaking or generating nonverbal vocalizations in response to external stimuli. The resulting assumption is that verbal and nonverbal vocal motor imagery activates neural systems that integrate the sensory-motor consequences of speech, even in the absence of primary motor cortical activity or sensory feedback. The present human functional magnetic resonance imaging study used univariate and multivariate analyses to investigate both overt and covert (internally generated) propositional and nonpropositional speech (noun definition and counting, respectively). Activity in response to overt, but not covert, speech was present in bilateral anterior PT, with no increased activity observed in posterior PT or parietal opercula for either speech type. On this evidence, the response of the left and right anterior PTs better fulfills the criteria for sensory target and state maps during overt speech production.

Dynamic reconfiguration of the language network preceding onset of speech in picture naming

Language production is a complex neural process that requires the interplay between multiple specialized cortical regions. We investigated modulations in large-scale cortical networks underlying preparation for speech production by contrasting cortico-cortical coherence for overt and silent picture naming in an all-to-all connectivity analysis. To capture transient, frequency-specific changes in functional connectivity we analyzed the magnetoencephalography data in two consecutive 300-ms time windows. Within the first 300 ms following picture onset beta frequency coherence was increased for overt naming in a network of regions comprising the bilateral parieto-temporal junction and medial cortices, suggesting that overt articulation modifies selection processes involved in speech planning. In the late time window (300-600 ms after picture onset) beta-range coherence was enhanced in a network that included the ventral sensorimotor and temporal cortices. Coherence in the gamma band was simultaneously reduced between the ventral motor cortex and supplementary motor area, bilaterally. The results suggest functionally distinct roles for beta (facilitatory) and gamma (suppressive) band interactions in speech production, with strong involvement of the motor cortex in both frequency bands. Overall, a striking difference in functional connectivity between the early and late time windows was observed, revealing the dynamic nature of large-scale cortical networks that support language and speech. Our results demonstrate that as the naming task evolves in time, the global connectivity patterns change, and that these changes occur (at least) on the time-scale of a few hundred milliseconds. More generally, these results bear implications for how we view large-scale neural networks underlying task performance.

The neural correlates of speech motor sequence learning

Speech is perhaps the most sophisticated example of a species-wide movement capability in the animal kingdom, requiring split-second sequencing of approximately 100 muscles in the respiratory, laryngeal, and oral movement systems. Despite the unique role speech plays in human interaction and the debilitating impact of its disruption, little is known about the neural mechanisms underlying speech motor learning. Here, we studied the behavioral and neural correlates of learning new speech motor sequences. Participants repeatedly produced novel, meaningless syllables comprising illegal consonant clusters (e.g., GVAZF) over 2 days of practice. Following practice, participants produced the sequences with fewer errors and shorter durations, indicative of motor learning. Using fMRI, we compared brain activity during production of the learned illegal sequences and novel illegal sequences. Greater activity was noted during production of novel sequences in brain regions linked to non-speech motor sequence learning, including the BG and pre-SMA. Activity during novel sequence production was also greater in brain regions associated with learning and maintaining speech motor programs, including lateral premotor cortex, frontal operculum, and posterior superior temporal cortex. Measures of learning success correlated positively with activity in left frontal operculum and white matter integrity under left posterior superior temporal sulcus. These findings indicate speech motor sequence learning relies not only on brain areas involved generally in motor sequencing learning but also those associated with feedback-based speech motor learning. Furthermore, learning success is modulated by the integrity of structural connectivity between these motor and sensory brain regions.

Decoding spectrotemporal features of overt and covert speech from the human cortex

Auditory perception and auditory imagery have been shown to activate overlapping brain regions. We hypothesized that these phenomena also share a common underlying neural representation. To assess this, we used electrocorticography intracranial recordings from epileptic patients performing an out loud or a silent reading task. In these tasks, short stories scrolled across a video screen in two conditions: subjects read the same stories both aloud (overt) and silently (covert). In a control condition the subject remained in a resting state. We first built a high gamma (70–150 Hz) neural decoding model to reconstruct spectrotemporal auditory features of self-generated overt speech. We then evaluated whether this same model could reconstruct auditory speech features in the covert speech condition. Two speech models were tested: a spectrogram and a modulation-based feature space. For the overt condition, reconstruction accuracy was evaluated as the correlation between original and predicted speech features, and was significant in each subject (p < 10⁻⁵; paired two-sample t-test). For the covert speech condition, dynamic time warping was first used to realign the covert speech reconstruction with the corresponding original speech from the overt condition. Reconstruction accuracy was then evaluated as the correlation between original and reconstructed speech features. Covert reconstruction accuracy was compared to the accuracy obtained from reconstructions in the baseline control condition. Reconstruction accuracy for the covert condition was significantly better than for the control condition (p < 0.005; paired two-sample t-test). The superior temporal gyrus, pre- and post-central gyrus provided the highest reconstruction information. The relationship between overt and covert speech reconstruction depended on anatomy. These results provide evidence that auditory representations of covert speech can be reconstructed from models that are built from an overt speech data set, supporting a partially shared neural substrate.

Neural decoding of single vowels during covert articulation using electrocorticography

The human brain has important abilities for manipulating phonemes, the basic building blocks of speech; these abilities represent phonological processing. Previous studies have shown change in the activation levels of broad cortical areas such as the premotor cortex, the inferior frontal gyrus, and the superior temporal gyrus during phonological processing. However, whether these areas actually convey signals to representations related to individual phonemes remains unclear. This study focused on single vowels and investigated cortical areas important for representing single vowels using electrocorticography (ECoG) during covert articulation. To identify such cortical areas, we used a neural decoding approach in which machine learning models identify vowels. A decoding model was trained on the ECoG signals from individual electrodes placed on the subjects' cortices. We then statistically evaluated whether each decoding model showed accurate identification of vowels, and we found cortical areas such as the premotor cortex and the superior temporal gyrus. These cortical areas were consistent with previous findings. On the other hand, no electrodes over Broca's area showed significant decoding accuracies. This was inconsistent with findings from a previous study showing that vowels within the phonemic sequence of words can be decoded using ECoG signals from Broca's area. Our results therefore suggest that Broca's area is involved in the processing of vowels within phonemic sequences, but not in the processing of single vowels.

Utility of a computerized, paced semantic verbal fluency paradigm in differentiating schizophrenia and healthy subjects

Functional magnetic resonance imaging (fMRI) paradigms designed to study word generation traditionally utilize a computerized paced version of the verbal fluency task (VFT) comprising 'blocks' of word generation and a baseline word repetition task. The utility of the above paced VFT paradigm in differentiating neuropsychiatric patients from healthy subjects has not been systematically examined. We administered a computerized, paced version of the semantic VFT comprising word generation and word repetition blocks to 24 schizophrenia and 24 matched healthy subjects, both before and during fMRI acquisition. The performance of patients with schizophrenia was significantly inferior to that of healthy control subjects in both the 'pre-scan' and 'intra-scan' sessions of the computerized paced semantic VFT. Specifically, schizophrenia patients generated significantly fewer total responses (VFTR) as well as correct responses (VFCR), but a larger number of 'no response' trials. However, there were no significant group differences in perseverative responses in the pre-scan session or 'intra-scan' sessions. The above computerized task has been reported by us previously to generate a behavioral performance index with hemodynamic correlates (John et al., 2011). Thus, our findings support the use of computerized paced VFT comprising word generation and word repetition blocks in both clinical and research settings.

A coordinate-based ALE functional MRI meta-analysis of brain activation during verbal fluency tasks in healthy control subjects

BACKGROUND

The processing of verbal fluency tasks relies on the coordinated activity of a number of brain areas, particularly in the frontal and temporal lobes of the left hemisphere. Recent studies using functional magnetic resonance imaging (fMRI) to study the neural networks subserving verbal fluency functions have yielded divergent results especially with respect to a parcellation of the inferior frontal gyrus for phonemic and semantic verbal fluency. We conducted a coordinate-based activation likelihood estimation (ALE) meta-analysis on brain activation during the processing of phonemic and semantic verbal fluency tasks involving 28 individual studies with 490 healthy volunteers.

RESULTS

For phonemic as well as for semantic verbal fluency, the most prominent clusters of brain activation were found in the left inferior/middle frontal gyrus (LIFG/MIFG) and the anterior cingulate gyrus. BA 44 was only involved in the processing of phonemic verbal fluency tasks, BA 45 and 47 in the processing of phonemic and semantic fluency tasks.

CONCLUSIONS

Our comparison of brain activation during the execution of either phonemic or semantic verbal fluency tasks revealed evidence for spatially different activation in BA 44, but not other regions of the LIFG/LMFG (BA 9, 45, 47) during phonemic and semantic verbal fluency processing.

What is that little voice inside my head? Inner speech phenomenology, its role in cognitive performance, and its relation to self-monitoring

The little voice inside our head, or inner speech, is a common everyday experience. It plays a central role in human consciousness at the interplay of language and thought. An impressive host of research works has been carried out on inner speech these last fifty years. Here we first describe the phenomenology of inner speech by examining five issues: common behavioural and cerebral correlates with overt speech, different types of inner speech (wilful verbal thought generation and verbal mind wandering), presence of inner speech in reading and in writing, inner signing and voice-hallucinations in deaf people. Secondly, we review the role of inner speech in cognitive performance (i.e., enhancement vs. perturbation). Finally, we consider agency in inner speech and how our inner voice is known to be self-generated and not produced by someone else.

Treating apraxia of speech with an implicit protocol that activates speech motor areas via inner speech

BACKGROUND

Treatments of apraxia of speech (AOS) have traditionally relied on overt practice. One alternative to this method is implicit phoneme manipulation which was derived from early models on inner speech. Implicit phoneme manipulation requires the participant to covertly move and combine phonemes to form a new word. This process engages a system of self-monitoring which is referred to as fully conscious inner speech.

AIMS

The present study aims to advance the understanding and validity of a new treatment for AOS, implicit phoneme manipulation. Tasks were designed to answer the following questions. 1. Would the practice of implicit phoneme manipulation improve the overt production of complex consonant blends in words? 2. Would this improvement generalize to untrained complex and simpler consonant blends in words? 3. Would these treatment tasks activate regions known to support motor planning and programming as verified by fMRI?

METHOD & PROCEDURES

The participant was asked to covertly manipulate phonemes to create a new word and to associate this newly formed word to a target picture among 4 phonologically-related choices. To avoid overt practice, probes were collected only after each block of training was completed. Probe sessions assessed the effects of implicit practice on the overt production of simple and complex consonant blends in words. An imaging protocol compared semantic baseline tasks to treatment tasks to verify that implicit phoneme manipulation activated brain regions of interest.

OUTCOMES & RESULTS

Behavioral: Response to implicit training of complex consonant blends resulted in improvements which were maintained 6 weeks after treatment. Further, this treatment generalized to simpler consonant blends in words. Imaging: Functional imaging during implicit phoneme manipulation showed significant activation in brain regions responsible for phonological processing when compared to the baseline semantic task.

CONCLUSIONS

Implicit phoneme manipulation offers an alternative to traditional methods that require overt production for treatment of AOS. Additionally, this implicit treatment method was shown to activate neural areas known to be involved in phonological processing, motor planning and programming.