目的探讨运动想象疗法对脑卒中患者运动功能康复的疗效。方法2015年5月至2016年10月,40例脑卒中偏瘫患者随机分为对照组(常规康复疗法)和运动想象组(运动想象+常规康复疗法),每组20例。治疗前及治疗6周后,分别采用Fugl-Meyer评定量表(FMA)、改良Barthel指数(MBI)进行评定,采用磁共振弥散张量成像(DTI)测量患者各向异性分数(FA)。结果治疗后,两组患者FMA评分、MBI评分均较治疗前显著提高(t>5.088, P<0.001),运动想象组优于对照组(t>2.124, P<0.05)。治疗前,两组病灶侧FA均较对侧明显减小(t>3.892, P<0.01),两组间无显著性差异(t<1.144, P>0.05);治疗后,运动想象组有较多患者(5/5 vs. 2/4) FA升高。结论运动想象疗法能促进脑卒中恢复期患者运动功能及日常生活活动能力恢复,对受损白质纤维的恢复可能有帮助。

Inner speech-also known as covert speech or verbal thinking-has been implicated in theories of cognitive development, speech monitoring, executive function, and psychopathology. Despite a growing body of knowledge on its phenomenology, development, and function, approaches to the scientific study of inner speech have remained diffuse and largely unintegrated. This review examines prominent theoretical approaches to inner speech and methodological challenges in its study, before reviewing current evidence on inner speech in children and adults from both typical and atypical populations. We conclude by considering prospects for an integrated cognitive science of inner speech, and present a multicomponent model of the phenomenon informed by developmental, cognitive, and psycholinguistic considerations. Despite its variability among individuals and across the life span, inner speech appears to perform significant functions in human cognition, which in some cases reflect its developmental origins and its sharing of resources with other cognitive processes.(c) 2015 APA, all rights reserved).

We hypothesized that areas in the temporal lobe that have been implicated in the phonological processing of spoken words would also be activated during the generation and phonological processing of imagined speech. We tested this hypothesis using functional magnetic resonance imaging during a behaviorally controlled task of metrical stress evaluation. Subjects were presented with bisyllabic words and had to determine the alternation of strong and weak syllables. Thus, they were required to discriminate between weak-initial words and strong-initial words. In one condition, the stimuli were presented auditorily to the subjects (by headphones). In the other condition the stimuli were presented visually on a screen and subjects were asked to imagine hearing the word. Results showed activation of the supplementary motor area, inferior frontal gyrus (Broca's area) and insula in both conditions. In the superior temporal gyrus (STG) and in the superior temporal sulcus (STS) strong activation was observed during the auditory (perceptual) condition. However, a region located in the posterior part of the STS/STG also responded during the imagery condition. No activation of this same region of the STS was observed during a control condition which also involved processing of visually presented words, but which required a semantic decision from the subject. We suggest that processing of metrical stress, with or without auditory input, relies in part on cortical interface systems located in the posterior part of STS/STG. These results corroborate behavioral evidence regarding phonological loop involvement in auditory-verbal imagery.

The assessment of brain function by blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) for tasks involving motion near the field of view is compromised by artifacts arising from the motion. The aim of this study is to demonstrate that these artifacts can be reduced by acquiring the average response from a brief stimulus (a "single-trial," or "event-related," paradigm) as opposed to alternating blocks of repeated task with rest (a "block-trial" paradigm). The basis of this technique is that the NMR signal changes from neuronal activation are delayed relative to the motion due to a slow hemodynamic response. By acquiring the average response from a brief stimulus, motion-induced signal changes occur prior to neuronal activation-induced signal changes, and the two can thus be distinguished. This technique is applied to the tasks of speaking out loud, swallowing, jaw clenching, and tongue movement. Functional activation maps derived from the single-trial paradigm contain significantly less artifact than functional activation maps derived from a more traditional block-trial paradigm.

Fluent speech comprises sequences that are composed from a finite alphabet of learned words, syllables, and phonemes. The sequencing of discrete motor behaviors has received much attention in the motor control literature, but relatively little has been focused directly on speech production. In this paper, we investigate the cortical and subcortical regions involved in organizing and enacting sequences of simple speech sounds. Sparse event-triggered functional magnetic resonance imaging (fMRI) was used to measure responses to preparation and overt production of non-lexical three-syllable utterances, parameterized by two factors: syllable complexity and sequence complexity. The comparison of overt production trials to preparation only trials revealed a network related to the initiation of a speech plan, control of the articulators, and to hearing one's own voice. This network included the primary motor and somatosensory cortices, auditory cortical areas, supplementary motor area (SMA), the precentral gyrus of the insula, and portions of the thalamus, basal ganglia, and cerebellum. Additional stimulus complexity led to increased engagement of the basic speech network and recruitment of additional areas known to be involved in sequencing non-speech motor acts. In particular, the left hemisphere inferior frontal sulcus and posterior parietal cortex, and bilateral regions at the junction of the anterior insula and frontal operculum, the SMA and pre-SMA, the basal ganglia, anterior thalamus, and the cerebellum showed increased activity for more complex stimuli. We hypothesize mechanistic roles for the extended speech production network in the organization and execution of sequences of speech sounds.

Motor imagery (MI) is the mental simulation of an action without any overt movement. Functional evidences show that brain activity during MI and motor execution (ME) largely overlaps. However, the role of the primary motor cortex (M1) during MI is controversial. Effective connectivity techniques show a facilitation on M1 during ME and an inhibition during MI, depending on whether an action should be performed or suppressed. Conversely, Transcranial Magnetic Stimulation (TMS) studies report facilitatory effects during both ME and MI. The present TMS study shed light on MI mechanisms, by manipulating the instructions given to the participants. In both Experimental and Control groups, participants were asked to mentally simulate a finger-thumb opposition task, but only the Experimental group received the explicit instruction to avoid any unwanted fingers movements. The amplitude of motor evoked potentials (MEPs) to TMS during MI was compared between the two groups. If the M1 facilitation actually pertains to MI per se, we should have expected to find it, irrespective of the instructions. Contrariwise, we found opposite results, showing facilitatory effects (increased MEPs amplitude) in the Control group and inhibitory effects (decreased MEPs amplitude) in the Experimental group. Control experiments demonstrated that the inhibitory effect was specific for the M1 contralateral to the hand performing the MI task and that the given instructions did not compromise the subjects' MI abilities. The present findings suggest a crucial role of motor inhibition when a "pure" MI task is performed and the subjects are explicitly instructed to avoid overt movements.Copyright © 2018 Elsevier Ltd. All rights reserved.

Retrieval of unintelligible speech is a basic need for speech impaired and is under research for several decades. But retrieval of random words from thoughts needs a substantial and consistent approach. This work focuses on the preliminary steps of retrieving vowels from Electroencephalography (EEG) signals acquired while speaking and imagining of speaking a consonant-vowel-consonant (CVC) word. The process, referred to as Speech imagery is imagining of speaking to oneself silently in the mind. Speech imagery is a form of mental imagery. Brain connectivity estimators such as EEG coherence, Partial Directed Coherence, Directed Transfer Function and Transfer Entropy have been used to estimate the concurrency and causal dependence (direction and strength) between different brain regions. From brain connectivity results it has been observed that the left frontal and left temporal electrodes were activated for speech and speech imagery processes. These brain connectivity estimators have been used for training Recurrent Neural Networks (RNN) and Deep Belief Networks (DBN) for identifying the vowel from the subject's thought. Though the accuracy level was found to be varying for each vowel while speaking and imagining of speaking the CVC word, the overall classification accuracy was found to be 72% while using RNN whereas a classification accuracy of 80% was observed while using DBN. DBN was found to outperform RNN in both the speech and speech imagery processes. Thus, the combination of brain connectivity estimators and deep learning techniques appear to be effective in identifying the vowel from EEG signals of subjects' thought.© Springer Nature B.V. 2019.

With the goal of providing a speech prosthesis for individuals with severe communication impairments, we propose a control scheme for brain-computer interfaces using vowel speech imagery. Electroencephalography was recorded in three healthy subjects for three tasks, imaginary speech of the English vowels /a/ and /u/, and a no action state as control. Trial averages revealed readiness potentials at 200 ms after stimulus and speech related potentials peaking after 350 ms. Spatial filters optimized for task discrimination were designed using the common spatial patterns method, and the resultant feature vectors were classified using a nonlinear support vector machine. Overall classification accuracies ranged from 68% to 78%. Results indicate significant potential for the use of vowel speech imagery as a speech prosthesis controller.

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.Copyright © 2020 Dash, Ferrari and Wang.

We used positron emission tomography (PET) to investigate brain regions associated with odor imagery. Changes in regional cerebral blood flow (CBF) during odor imagery were compared with changes during nonspecific expectation of olfactory stimuli and with those during odor perception. Sixty-seven healthy volunteers were screened for their odor imagery (with a paradigm developed in a previous study), and 12 of them, assessed to be "good odor imagers," participated in the neuroimaging part of the study. Imagination of odors was associated with increased activation in several olfactory regions in the brain: the left primary olfactory cortical (POC) region including piriform cortex, the left secondary olfactory cortex or posterior orbitofrontal cortex (OFC), and the rostral insula bilaterally. Furthermore, blood flow in two regions within the right orbitofrontal cortex correlated significantly with the behavioral measure of odor imagery during scanning. Overall, the findings indicated that neural networks engaged during odor perception and imagery overlap partially.

We investigate whether imagery of voluntary movements of different body parts activates somatotopical sections of the human motor cortices. We used functional magnetic resonance imaging to detect the cortical activity when 7 healthy subjects imagine performing repetitive (0.5-Hz) flexion/extension movements of the right fingers or right toes, or horizontal movements of the tongue. We also collected functional images when the subjects actually executed these movements and used these data to define somatotopical representations in the motor areas. In this study, we relate the functional activation maps to cytoarchitectural population maps of areas 4a, 4p, and 6 in the same standard anatomical space. The important novel findings are 1). that imagery of hand movements specifically activates the hand sections of the contralateral primary motor cortex (area 4a) and the contralateral dorsal premotor cortex (area 6) and a hand representation located in the caudal cingulate motor area and the most ventral part of the supplementary motor area; 2). that when imagining making foot movements, the foot zones of the posterior part of the contralateral supplementary motor area (area 6) and the contralateral primary motor cortex (area 4a) are active; and 3). that imagery of tongue movements activates the tongue region of the primary motor cortex and the premotor cortex bilaterally (areas 4a, 4p, and 6). These results demonstrate that imagery of action engages the somatotopically organized sections of the primary motor cortex in a systematic manner as well as activating some body-part-specific representations in the nonprimary motor areas. Thus the content of the mental motor image, in this case the body part, is reflected in the pattern of motor cortical activation.

Many individuals with aphasia describe anomia with comments like "I know it but I can't say it." The exact meaning of such phrases is unclear. We hypothesize that at least two discrete experiences exist: the sense of (1) knowing a concept, but failing to find the right word, and (2) saying the correct word internally but not aloud (successful inner speech, sIS). We propose that sIS reflects successful lexical access; subsequent overt anomia indicates post-lexical output deficits. In this pilot study, we probed the subjective experience of anomia in 37 persons with aphasia. Self-reported sIS related to aphasia severity and phonological output deficits. In multivariate lesion-symptom mapping, sIS was associated with dorsal stream lesions, particularly in ventral sensorimotor cortex. These preliminary results suggest that people with aphasia can often provide meaningful insights about their experience of anomia and that reports of sIS relate to specific lesion locations and language deficits.Copyright © 2016 Elsevier Inc. All rights reserved.

Broca's area in the posterior half of the left inferior frontal gyrus has long been thought to be critical for speech production. The current view is that long-term speech production outcome in patients with Broca's area damage is best explained by the combination of damage to Broca's area and neighbouring regions including the underlying white matter, which was also damaged in Paul Broca's two historic cases. Here, we dissociate the effect of damage to Broca's area from the effect of damage to surrounding areas by studying long-term speech production outcome in 134 stroke survivors with relatively circumscribed left frontal lobe lesions that spared posterior speech production areas in lateral inferior parietal and superior temporal association cortices. Collectively, these patients had varying degrees of damage to one or more of nine atlas-based grey or white matter regions: Brodmann areas 44 and 45 (together known as Broca's area), ventral premotor cortex, primary motor cortex, insula, putamen, the anterior segment of the arcuate fasciculus, uncinate fasciculus and frontal aslant tract. Spoken picture description scores from the Comprehensive Aphasia Test were used as the outcome measure. Multiple regression analyses allowed us to tease apart the contribution of other variables influencing speech production abilities such as total lesion volume and time post-stroke. We found that, in our sample of patients with left frontal damage, long-term speech production impairments (lasting beyond 3 months post-stroke) were solely predicted by the degree of damage to white matter, directly above the insula, in the vicinity of the anterior part of the arcuate fasciculus, with no contribution from the degree of damage to Broca's area (as confirmed with Bayesian statistics). The effect of white matter damage cannot be explained by a disconnection of Broca's area, because speech production scores were worse after damage to the anterior arcuate fasciculus with relative sparing of Broca's area than after damage to Broca's area with relative sparing of the anterior arcuate fasciculus. Our findings provide evidence for three novel conclusions: (i) Broca's area damage does not contribute to long-term speech production outcome after left frontal lobe strokes; (ii) persistent speech production impairments after damage to the anterior arcuate fasciculus cannot be explained by a disconnection of Broca's area; and (iii) the prior association between persistent speech production impairments and Broca's area damage can be explained by co-occurring white matter damage, above the insula, in the vicinity of the anterior part of the arcuate fasciculus.© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.

Neuroimaging studies have demonstrated that mental imagery and perception share similar neural substrates, however, there are still ambiguities according to different auditory imagery content. In addition, there is still a lack of information regarding the underlying neural correlation between the two modalities. In the present study, we adopted functional magnetic resonance imaging to explore the neural representation during imagery and perception of actual sounds in our surroundings. Univariate analysis was used to assess the differences between the modalities of average activation intensity, and stronger imagery activation was found in sensorimotor regions but weaker activation in auditory association cortices. Additionally, multi-voxel pattern analysis with a support vector machine classifier was implemented to decode environmental sounds within- or cross-modality. Significant above-chance accuracies were found in all overlapping regions in the classification of within-modality, while successful cross-modality classification only was found in sensorimotor regions. Both univariate and multivariate analyses found distinct representation between auditory imagery and perception in the overlapping regions, including superior temporal gyrus and inferior frontal sulcus as well as the precentral cortex and pre-supplementary motor area. Our results confirm the overlapping activation regions between auditory imagery and perception reported by previous studies and suggest that activation regions showed dissociable representation pattern in imagery and perception of sound categories.

This article describes a neural network model that addresses the acquisition of speaking skills by infants and subsequent motor equivalent production of speech sounds. The model learns two mappings during a babbling phase. A phonetic-to-orosensory mapping specifies a vocal tract target for each speech sound; these targets take the form of convex regions in orosensory coordinates defining the shape of the vocal tract. The babbling process wherein these convex region targets are formed explains how an infant can learn phoneme-specific and language-specific limits on acceptable variability of articulator movements. The model also learns an orosensory-to-articulatory mapping wherein cells coding desired movement directions in orosensory space learn articulator movements that achieve these orosensory movement directions. The resulting mapping provides a natural explanation for the formation of coordinative structures. This mapping also makes efficient use of redundancy in the articulator system, thereby providing the model with motor equivalent capabilities. Simulations verify the model's ability to compensate for constraints or perturbations applied to the articulators automatically and without new learning and to explain contextual variability seen in human speech production.

This article describes a neural network model of speech motor skill acquisition and speech production that explains a wide range of data on variability, motor equivalence, coarticulation, and rate effects. Model parameters are learned during a babbling phase. To explain how infants learn language-specific variability limits, speech sound targets take the form of convex regions, rather than points, in orosensory coordinates. Reducing target size for better accuracy during slower speech leads to differential effects for vowels and consonants, as seen in experiments previously used as evidence for separate control processes for the 2 sound types. Anticipatory coarticulation arises when targets are reduced in size on the basis of context; this generalizes the well-known look-ahead model of coarticulation. Computer simulations verify the model's properties.

Speech production involves the integration of auditory, somatosensory, and motor information in the brain. This article describes a model of speech motor control in which a feedforward control system, involving premotor and primary motor cortex and the cerebellum, works in concert with auditory and somatosensory feedback control systems that involve both sensory and motor cortical areas. New speech sounds are learned by first storing an auditory target for the sound, then using the auditory feedback control system to control production of the sound in early repetitions. Repeated production of the sound leads to tuning of feedforward commands which eventually supplant the feedback-based control signals. Although parts of the model remain speculative, it accounts for a wide range of kinematic, acoustic, and neuroimaging data collected during speech production and provides a framework for investigating communication disorders that involve malfunction of the cerebral cortex and interconnected subcortical structures.Readers will be able to: (1) describe several types of learning that occur in the sensory-motor system during babbling and early speech, (2) identify three neural control subsystems involved in speech production, (3) identify regions of the brain involved in monitoring auditory and somatosensory feedback during speech production, and (4) identify regions of the brain involved in feedforward control of speech.

This paper describes a neural model of speech acquisition and production that accounts for a wide range of acoustic, kinematic, and neuroimaging data concerning the control of speech movements. The model is a neural network whose components correspond to regions of the cerebral cortex and cerebellum, including premotor, motor, auditory, and somatosensory cortical areas. Computer simulations of the model verify its ability to account for compensation to lip and jaw perturbations during speech. Specific anatomical locations of the model's components are estimated, and these estimates are used to simulate fMRI experiments of simple syllable production.

This article describes a computational model, called DIVA, that provides a quantitative framework for understanding the roles of various brain regions involved in speech acquisition and production. An overview of the DIVA model is first provided, along with descriptions of the computations performed in the different brain regions represented in the model. Particular focus is given to the model's speech sound map, which provides a link between the sensory representation of a speech sound and the motor program for that sound. Neurons in this map share with "mirror neurons" described in monkey ventral premotor cortex the key property of being active during both production and perception of specific motor actions. As the DIVA model is defined both computationally and anatomically, it is ideal for generating precise predictions concerning speech-related brain activation patterns observed during functional imaging experiments. The DIVA model thus provides a well-defined framework for guiding the interpretation of experimental results related to the putative human speech mirror system.

Motor imagery has recently gained attention as a promising new rehabilitation method for patients with neurological disorders. Up to now, however, it has been unclear whether this practice method can also be successfully applied in the rehabilitation of patients with Parkinson disease (PD).This study aimed to investigate whether the motor imagery ability of patients with PD is still intact despite basal ganglia dysfunctioning.A total of 14 patients with early- and mid-stage PD (Hoehn and Yahr 1-3) and 14 healthy controls were evaluated by means of an extensive imagery ability assessment battery, consisting of 2 questionnaires, the Chaotic Motor Imagery Assessment battery, and a test based on mental chronometry.PD patients performed the imagery tasks more slowly than controls, but the motor imagery vividness and accuracy of most patients were well preserved.These results are promising regarding the potential use of motor imagery practice in the rehabilitation of patients with PD.

Sensorimotor integration is an active domain of speech research and is characterized by two main ideas, that the auditory system is critically involved in speech production and that the motor system is critically involved in speech perception. Despite the complementarity of these ideas, there is little crosstalk between these literatures. We propose an integrative model of the speech-related "dorsal stream" in which sensorimotor interaction primarily supports speech production, in the form of a state feedback control architecture. A critical component of this control system is forward sensory prediction, which affords a natural mechanism for limited motor influence on perception, as recent perceptual research has suggested. Evidence shows that this influence is modulatory but not necessary for speech perception. The neuroanatomy of the proposed circuit is discussed as well as some probable clinical correlates including conduction aphasia, stuttering, and aspects of schizophrenia.Copyright © 2011 Elsevier Inc. All rights reserved.

Spoken language exists because of a remarkable neural process. Inside a speaker's brain, an intended message gives rise to neural signals activating the muscles of the vocal tract. The process is remarkable because these muscles are activated in just the right way that the vocal tract produces sounds a listener understands as the intended message. What is the best approach to understanding the neural substrate of this crucial motor control process? One of the key recent modeling developments in neuroscience has been the use of state feedback control (SFC) theory to explain the role of the CNS in motor control. SFC postulates that the CNS controls motor output by (1) estimating the current dynamic state of the thing (e. g., arm) being controlled, and (2) generating controls based on this estimated state. SFC has successfully predicted a great range of non-speech motor phenomena, but as yet has not received attention in the speech motor control community. Here, we review some of the key characteristics of speech motor control and what they say about the role of the CNS in the process. We then discuss prior efforts to model the role of CNS in speech motor control, and argue that these models have inherent limitations - limitations that are overcome by an SFC model of speech motor control which we describe. We conclude by discussing a plausible neural substrate of our model.

Word production begins with high-Gamma automatic linguistic processing functions followed by speech motor planning and articulation. Phonetic properties are processed in both linguistic and motor stages of word production. Four phonetically dissimilar phonemic structures "BA", "FO", "LE", and "RY" were chosen as covert speech tasks. Ten neurologically healthy volunteers with the age range of 21-33 participated in this experiment. Participants were asked to covertly speak a phonemic structure when they heard an auditory cue. EEG was recorded with 64 electrodes at 2048 samples/s. Initially, one-second trials were used, which contained linguistic and motor imagery activities. The four-class true positive rate was calculated. In the next stage, 312 ms trials were used to exclude covert articulation from analysis. By eliminating the covert articulation stage, the four-class grand average classification accuracy dropped from 96.4% to 94.5%. The most valuable features emerge after Auditory cue recognition (~100 ms post onset), and within the 70-128 Hz frequency range. The most significant identified brain regions were the Prefrontal Cortex (linked to stimulus driven executive control), Wernicke's area (linked to Phonological code retrieval), the right IFG, and Broca's area (linked to syllabification). Alpha and Beta band oscillations associated with motor imagery do not contain enough information to fully reflect the complexity of speech movements. Over 90% of the most class-dependent features were in the 30-128 Hz range, even during the covert articulation stage. As a result, compared to linguistic functions, the contribution of motor imagery of articulation in class separability of covert speech tasks from EEG data is negligible.

This perspective describes predictive processing as a computational framework for understanding cortical function in the context of emerging evidence, with a focus on sensory processing. We discuss how the predictive processing framework may be implemented at the level of cortical circuits and how its implementation could be falsified experimentally. Lastly, we summarize the general implications of predictive processing on cortical function in healthy and diseased states.Copyright © 2018 Elsevier Inc. All rights reserved.

Aphasia results both from direct effects of focal damage to eloquent cortical areas as well as dysfunction of interconnected remote areas within the language network. Resting-state functional MRI (rsfMRI) can be used to examine functional connectivity (FC) within these networks. Herein we review publications, which applied rsfMRI to understand network pathology in post stroke aphasia. A common finding in this research is an acute disruption of connectivity within the language network, which is correlated with loss of language function and tends to resolve with recovery from aphasia. All studies are limited by small sample sizes, heterogeneous patient characteristics and a wide range of analytical approaches, which further hinder deduction of common patterns across studies. One recent large-scale study examining FC and behavior across various cognitive domains, however, has made substantial progress with the description of a "network phenotype of stroke injury", which consists of a disruption of interhemispheric connectivity and reduced segregation of intrahemispheric networks. Unlike in other domains, language functions showed substantial dependence on intact left intrahemispheric connectivity (Siegel, Ramsey et al., 2016). In the future, such analyses of network pathology might support prognosis and development of effective treatment strategies in individual patients with aphasia.Copyright © 2017 Elsevier Inc. All rights reserved.

Despite the ubiquity of inner speech in our mental lives, methods for objectively assessing inner speech capacities remain underdeveloped. The most common means of assessing inner speech is to present participants with tasks requiring them to silently judge whether two words rhyme. We developed a version of this task to assess the inner speech of a population of patients with aphasia and corresponding language production deficits. Patients' performance on the silent rhyming task was severely impaired relative to controls. Patients' performance on this task did not, however, correlate with their performance on a variety of other standard tests of overt language and rhyming abilities. In particular, patients who were generally unimpaired in their abilities to overtly name objects during confrontation naming tasks, and who could reliably judge when two words spoken to them rhymed, were still severely impaired (relative to controls) at completing the silent rhyme task. A variety of explanations for these results are considered, as a means to critically reflecting on the relations among inner speech, outer speech, and silent rhyme judgments more generally.

To provide evidence that motor imagery (MI) is accompanied by improvement of intramuscular conduction velocity (CV), we investigated surface electromyographic (EMG) activity of 3 muscles during the elbow flexion/extension. Thirty right-handed participants were asked to lift or to imagine lifting a weighted dumbbell under 3 types of muscular contractions, i.e. concentric, isometric and eccentric, taken as independent variables. The EMG activity of the agonist (long and short heads of biceps brachii) and the antagonist (long portion of triceps brachii) muscles was recorded and processed to determine the median frequency (MF) of EMG power spectrum as dependant variable. The MF was significantly higher during the MI sessions than during the resting condition while the participants remained strictly motionless. Moreover, the MF during imagined concentric contraction was significantly higher than during the eccentric. Thus, the MF variation was correlated to the type of contraction the muscle produced. During MI, the EMG patterns corresponding to each type of muscle contraction remained comparable to those observed during actual movement. In conclusion, specific motor programming is hypothesized to be performed as a function of muscle contraction type during MI.

Motor imagery is the mental representation of an action without overt movement or muscle activation. However, the effects of motor imagery on stroke-induced hand dysfunction and brain neural networks are still unknown. We conducted a randomized controlled trial in the China Rehabilitation Research Center. Twenty stroke patients, including 13 males and 7 females, 32-51 years old, were recruited and randomly assigned to the traditional rehabilitation treatment group (PP group, n = 10) or the motor imagery training combined with traditional rehabilitation treatment group (MP group, n = 10). All patients received rehabilitation training once a day, 45 minutes per session, five times per week, for 4 consecutive weeks. In the MP group, motor imagery training was performed for 45 minutes after traditional rehabilitation training, daily. Action Research Arm Test and the Fugl-Meyer Assessment of the upper extremity were used to evaluate hand functions before and after treatment. Transcranial magnetic stimulation was used to analyze motor evoked potentials in the affected extremity. Diffusion tensor imaging was used to assess changes in brain neural networks. Compared with the PP group, the MP group showed better recovery of hand function, higher amplitude of the motor evoked potential in the abductor pollicis brevis, greater fractional anisotropy of the right dorsal pathway, and an increase in the fractional anisotropy of the bilateral dorsal pathway. Our findings indicate that 4 weeks of motor imagery training combined with traditional rehabilitation treatment improves hand function in stroke patients by enhancing the dorsal pathway. This trial has been registered with the Chinese Clinical Trial Registry (registration number: ChiCTR-OCH-12002238).

The aim of this study was to examine the specificity of motor imagery (MI) difficulties in children with CP.Performance of 22 children with CP was compared to a gender and age matched control group. MI ability was measured with the Hand Laterality Judgment (HLJ) task, examining specifically the direction of rotation (DOR) effect, and the Praxis Imagery Questionnaire (PIQ).In the back view condition of the HLJ task both groups used MI, as evidenced by longer response times for lateral compared with medial rotational angles. In the palm view condition children with CP did not show an effect of DOR, unlike controls. Error scores did not differ between groups. Both groups performed well on the PIQ, with no significant difference between them in response pattern.The present study suggests that children with CP show deficits on tasks that trigger implicit use of MI, whereas explicit MI ability was relatively preserved, as assessed using the PIQ. These results suggest that employing more explicit methods of MI training may well be more suitable for children with CP in rehabilitation of motor function.Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

It has been proposed that motor imagery contains an element of sensory experiences (kinesthetic sensations), which is a substitute for the sensory feedback that would normally arise from the overt action. No evidence has been provided about whether kinesthetic sensation is centrally simulated during motor imagery. We psychophysically tested whether motor imagery of palmar flexion or dorsiflexion of the right wrist would influence the sensation of illusory palmar flexion elicited by tendon vibration. We also tested whether motor imagery of wrist movement shared the same neural substrates involving the illusory sensation elicited by the peripheral stimuli. Regional cerebral blood flow was measured with H215O and positron emission tomography in 10 right-handed subjects. The right tendon of the wrist extensor was vibrated at 83 Hz ("illusion") or at 12.5 Hz with no illusion ("vibration"). Subjects imagined doing wrist movements of alternating palmar and dorsiflexion at the same speed with the experienced illusory movements ("imagery"). A "rest" condition with eyes closed was included. We identified common active fields between the contrasts of imagery versus rest and illusion versus vibration. Motor imagery of palmar flexion psychophysically enhanced the experienced illusory angles of plamar flexion, whereas dorsiflexion imagery reduced it in the absence of overt movement. Motor imagery and the illusory sensation commonly activated the contralateral cingulate motor areas, supplementary motor area, dorsal premotor cortex, and ipsilateral cerebellum. We conclude that kinesthetic sensation associated with imagined movement is internally simulated during motor imagery by recruiting multiple motor areas.

A neuronal sign of persistent developmental stuttering is the magnified coactivation of right frontal brain regions during speech production. Whether and how stuttering severity relates to the connection strength of these hyperactive right frontal areas to other brain areas is an open question. Scrutinizing such brain-behaviour and structure-function relationships aims at disentangling suspected underlying neuronal mechanisms of stuttering. Here, we acquired diffusion-weighted and functional images from 31 adults who stutter and 34 matched control participants. Using a newly developed structural connectivity measure, we calculated voxel-wise correlations between connection strength and stuttering severity within tract volumes that originated from functionally hyperactive right frontal regions. Correlation analyses revealed that with increasing speech motor deficits the connection strength increased in the right frontal aslant tract, the right anterior thalamic radiation, and in U-shaped projections underneath the right precentral sulcus. In contrast, with decreasing speech motor deficits connection strength increased in the right uncinate fasciculus. Additional group comparisons of whole-brain white matter skeletons replicated the previously reported reduction of fractional anisotropy in the left and right superior longitudinal fasciculus as well as at the junction of right frontal aslant tract and right superior longitudinal fasciculus in adults who stutter compared to control participants. Overall, our investigation suggests that right fronto-temporal networks play a compensatory role as a fluency enhancing mechanism. In contrast, the increased connection strength within subcortical-cortical pathways may be implied in an overly active global response suppression mechanism in stuttering. Altogether, this combined functional MRI-diffusion tensor imaging study disentangles different networks involved in the neuronal underpinnings of the speech motor deficit in persistent developmental stuttering.© The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.

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.Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

The cerebellum has been hypothesized to form a crucial part of the speech motor control network. Evidence for this comes from patients with cerebellar damage, who exhibit a variety of speech deficits, as well as imaging studies showing cerebellar activation during speech production in healthy individuals. To date, the precise role of the cerebellum in speech motor control remains unclear, as it has been implicated in both anticipatory (feedforward) and reactive (feedback) control. Here, we assess both anticipatory and reactive aspects of speech motor control, comparing the performance of patients with cerebellar degeneration and matched controls. Experiment 1 tested feedforward control by examining speech adaptation across trials in response to a consistent perturbation of auditory feedback. Experiment 2 tested feedback control, examining online corrections in response to inconsistent perturbations of auditory feedback. Both male and female patients and controls were tested. The patients were impaired in adapting their feedforward control system relative to controls, exhibiting an attenuated anticipatory response to the perturbation. In contrast, the patients produced even larger compensatory responses than controls, suggesting an increased reliance on sensory feedback to guide speech articulation in this population. Together, these results suggest that the cerebellum is crucial for maintaining accurate feedforward control of speech, but relatively uninvolved in feedback control. Speech motor control is a complex activity that is thought to rely on both predictive, feedforward control as well as reactive, feedback control. While the cerebellum has been shown to be part of the speech motor control network, its functional contribution to feedback and feedforward control remains controversial. Here, we use real-time auditory perturbations of speech to show that patients with cerebellar degeneration are impaired in adapting feedforward control of speech but retain the ability to make online feedback corrections; indeed, the patients show an increased sensitivity to feedback. These results indicate that the cerebellum forms a crucial part of the feedforward control system for speech but is not essential for online, feedback control.Copyright © 2017 the authors 0270-6474/17/379249-10$15.00/0.

Mental imagery can be advantageous, unnecessary and even clinically disruptive. With methodological constraints now overcome, research has shown that visual imagery involves a network of brain areas from the frontal cortex to sensory areas, overlapping with the default mode network, and can function much like a weak version of afferent perception. Imagery vividness and strength range from completely absent (aphantasia) to photo-like (hyperphantasia). Both the anatomy and function of the primary visual cortex are related to visual imagery. The use of imagery as a tool has been linked to many compound cognitive processes and imagery plays both symptomatic and mechanistic roles in neurological and mental disorders and treatments.

Language is one of the defining abilities of humans. Many studies have characterized the neural correlates of different aspects of language processing. However, the imaging techniques typically used in these studies were limited in either their temporal or spatial resolution. Electrocorticographic (ECoG) recordings from the surface of the brain combine high spatial with high temporal resolution and thus could be a valuable tool for the study of neural correlates of language function. In this study, we defined the spatiotemporal dynamics of ECoG activity during a word repetition task in nine human subjects. ECoG was recorded while each subject overtly or covertly repeated words that were presented either visually or auditorily. ECoG amplitudes in the high gamma (HG) band confidently tracked neural changes associated with stimulus presentation and with the subject's verbal response. Overt word production was primarily associated with HG changes in the superior and middle parts of temporal lobe, Wernicke's area, the supramarginal gyrus, Broca's area, premotor cortex (PMC), primary motor cortex. Covert word production was primarily associated with HG changes in superior temporal lobe and the supramarginal gyrus. Acoustic processing from both auditory stimuli as well as the subject's own voice resulted in HG power changes in superior temporal lobe and Wernicke's area. In summary, this study represents a comprehensive characterization of overt and covert speech using electrophysiological imaging with high spatial and temporal resolution. It thereby complements the findings of previous neuroimaging studies of language and thus further adds to current understanding of word processing in humans.Published by Elsevier Inc.

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.Copyright © 2014 Elsevier B.V. All rights reserved.

There is growing awareness that aphasia following a stroke can include deficits in other cognitive functions and that these are predictive of certain aspects of language function, recovery and rehabilitation. However, data on attentional and executive (dys)functions in individuals with stroke aphasia are still scarce and the relationship to underlying lesions is rarely explored. Accordingly in this investigation, an extensive selection of standardized non-verbal neuropsychological tests was administered to 38 individuals with chronic post-stroke aphasia, in addition to detailed language testing and MRI. To establish the core components underlying the variable patients' performance, behavioural data were explored with rotated principal component analyses, first separately for the non-verbal and language tests, then in a combined analysis including all tests. Three orthogonal components for the non-verbal tests were extracted, which were interpreted as shift-update, inhibit-generate and speed. Three components were also extracted for the language tests, representing phonology, semantics and speech quanta. Individual continuous scores on each component were then included in a voxel-based correlational methodology analysis, yielding significant clusters for all components. The shift-update component was associated with a posterior left temporo-occipital and bilateral medial parietal cluster, the inhibit-generate component was mainly associated with left frontal and bilateral medial frontal regions, and the speed component with several small right-sided fronto-parieto-occipital clusters. Two complementary multivariate brain-behaviour mapping methods were also used, which showed converging results. Together the results suggest that a range of brain regions are involved in attention and executive functioning, and that these non-language domains play a role in the abilities of patients with chronic aphasia. In conclusion, our findings confirm and extend our understanding of the multidimensionality of stroke aphasia, emphasize the importance of assessing non-verbal cognition in this patient group and provide directions for future research and clinical practice. We also briefly compare and discuss univariate and multivariate methods for brain-behaviour mapping.© The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain.

We used functional MRI to examine the functional anatomy of inner speech and different forms of auditory verbal imagery (imagining speech) in normal volunteers. We hypothesized that generating inner speech and auditory verbal imagery would be associated with left inferior frontal activation, and that generating auditory verbal imagery would involve additional activation in the lateral temporal cortices.Subjects were scanned, while performing inner speech and auditory verbal imagery tasks, using a 1.5 Tesla magnet.The generation of inner speech was associated with activation in the left inferior frontal/insula region, the left temporo-parietal cortex, right cerebellum and the supplementary motor area. Auditory verbal imagery in general, as indexed by the three imagery tasks combined, was associated with activation in the areas engaged during the inner speech task, plus the left precentral and superior temporal gyri (STG), and the right homologues of all these areas.These results are consistent with the use of the 'articulatory loop' during both inner speech and auditory verbal imagery, and the greater engagement of verbal self-monitoring during auditory verbal imagery.

The paradigmatic assumption that REM sleep is the physiological equivalent of dreaming is in need of fundamental revision. A mounting body of evidence suggests that dreaming and REM sleep are dissociable states, and that dreaming is controlled by forebrain mechanisms. Recent neuropsychological, radiological, and pharmacological findings suggest that the cholinergic brain stem mechanisms that control the REM state can only generate the psychological phenomena of dreaming through the mediation of a second, probably dopaminergic, forebrain mechanism. The latter mechanism (and thus dreaming itself) can also be activated by a variety of nonREM triggers. Dreaming can be manipulated by dopamine agonists and antagonists with no concomitant change in REM frequency, duration, and density. Dreaming can also be induced by focal forebrain stimulation and by complex partial (forebrain) seizures during nonREM sleep, when the involvement of brainstem REM mechanisms is precluded. Likewise, dreaming is obliterated by focal lesions along a specific (probably dopaminergic) forebrain pathway, and these lesions do not have any appreciable effects on REM frequency, duration, and density. These findings suggest that the forebrain mechanism in question is the final common path to dreaming and that the brainstem oscillator that controls the REM state is just one of the many arousal triggers that can activate this forebrain mechanism. The "REM-on" mechanism (like its various NREM equivalents) therefore stands outside the dream process itself, which is mediated by an independent, forebrain "dream-on" mechanism.

Functional near-infrared spectroscopy (fNIRS) is an emerging technique for measuring changes in cerebral hemoglobin concentration via optical absorption changes. Although there is great interest in using fNIRS to study brain connectivity, current methods are unable to infer the directionality of neuronal connections. In this paper, we apply Dynamic Causal Modelling (DCM) to fNIRS data. Specifically, we present a generative model of how observed fNIRS data are caused by interactions among hidden neuronal states. Inversion of this generative model, using an established Bayesian framework (variational Laplace), then enables inference about changes in directed connectivity at the neuronal level. Using experimental data acquired during motor imagery and motor execution tasks, we show that directed (i.e., effective) connectivity from the supplementary motor area to the primary motor cortex is negatively modulated by motor imagery, and this suppressive influence causes reduced activity in the primary motor cortex during motor imagery. These results are consistent with findings of previous functional magnetic resonance imaging (fMRI) studies, suggesting that the proposed method enables one to infer directed interactions in the brain mediated by neuronal dynamics from measurements of optical density changes. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

The classical concept of efference copies in the context of internal forward models has stimulated productive research in cognitive science and neuroscience. There are compelling reasons to argue for such a mechanism, but finding direct evidence in the human brain remains difficult. Here we investigate the dynamics of internal forward models from an unconventional angle: mental imagery, assessed while recording high temporal resolution neuronal activity using magnetoencephalography. We compare two overt and covert tasks; our covert, mental imagery tasks are unconfounded by overt input/output demands - but in turn necessitate the development of appropriate multi-dimensional topographic analyses. Finger tapping (studies 1 and 2) and speech experiments (studies 3-5) provide temporally constrained results that implicate the estimation of an efference copy. We suggest that one internal forward model over parietal cortex subserves the kinesthetic feeling in motor imagery. Secondly, observed auditory neural activity similar to 170 ms after motor estimation in speech experiments (studies 3-5) demonstrates the anticipated auditory consequences of planned motor commands in a second internal forward model in imagery of speech production. Our results provide neurophysiological evidence from the human brain in favor of internal forward models deploying efference copies in somatosensory and auditory cortex, in finger tapping and speech production tasks, respectively, and also suggest the dynamics and sequential updating structure of internal forward models.

The neural basis of mental imagery has been investigated by localizing the underlying neural networks, mostly in motor and perceptual systems, separately. However, how modality-specific representations are top-down induced and how the action and perception systems interact in the context of mental imagery is not well understood. Imagined speech production ("articulation imagery"), which induces the kinesthetic feeling of articulator movement and its auditory consequences, provides a new angle because of the concurrent involvement of motor and perceptual systems. On the basis of previous findings in mental imagery of speech, we argue for the following regarding the induction mechanisms of mental imagery and the interaction between motor and perceptual systems: (1) Two distinct top-down mechanisms, memory retrieval and motor simulation, exist to induce estimation in perceptual systems. (2) Motor simulation is sufficient to internally induce the representation of perceptual changes that would be caused by actual movement (perceptual associations); however, this simulation process only has modulatory effects on the perception of external stimuli, which critically depends on context and task demands. Considering the proposed simulation-estimation processes as common mechanisms for interaction between motor and perceptual systems, we outline how mental imagery (of speech) relates to perception and production, and how these hypothesized mechanisms might underpin certain neural disorders.

A critical subroutine of self-monitoring during speech production is to detect any deviance between expected and actual auditory feedback. Here we investigated the associated neural dynamics using MEG recording in mental-imagery-of-speech paradigms. Participants covertly articulated the vowel /a/; their own (individually recorded) speech was played back, with parametric manipulation using four levels of pitch shift, crossed with four levels of onset delay. A nonmonotonic function was observed in early auditory responses when the onset delay was shorter than 100 msec: Suppression was observed for normal playback, but enhancement for pitch-shifted playback; however, the magnitude of enhancement decreased at the largest level of pitch shift that was out of pitch range for normal conversion, as suggested in two behavioral experiments. No difference was observed among different types of playback when the onset delay was longer than 100 msec. These results suggest that the prediction suppresses the response to normal feedback, which mediates source monitoring. When auditory feedback does not match the prediction, an "error term" is generated, which underlies deviance detection. We argue that, based on the observed nonmonotonic function, a frequency window (addressing spectral difference) and a time window (constraining temporal difference) jointly regulate the comparison between prediction and feedback in speech.