The effect of set on the resting state in functional imaging: a role for the striatum?

Cerebral Blood Flow Is Not a Direct Surrogate of Behavior: Performance Models Suggest a Role for Functional Meta-Networks

Background

Functional brain imaging has become the dominant approach to the study of brain-behavior relationships. Unfortunately, the behavior half of the equation has been relegated to second-class status when it is not ignored completely. Different approaches to connectivity, based on temporally correlated physiological events across the brain, have ascended in place of behavior. A performance-based analysis has been developed as a simple, basic approach to incorporating specific performance measures obtained during imaging into the analysis of the imaging data identifying clinically relevant regions.

Methods

This paper contrasts performance-based lateralized regional cerebral blood flow (CBF) predictors of speech rate during Positron Emission Tomography with the values of these regions and their opposite hemisphere homologs in which a performance-based model was not applied. Five studies were examined: two that utilized normal speakers, one that utilized ataxic speakers, and two that examined Parkinsonian speakers.

Results

In each study, the predictors were lateralized but the blood flow values that contributed to the performance-based analysis were bilateral. The speech-rate predictor regions were consistent with clinical studies on the effects of focal brain damage.

Conclusions

This approach has identified a basic, reproducible blood flow network that has predicted speech rate in multiple normal and neurologic groups. While the predictors are lateralized consistent with lesion data, the blood flow values of these regions are neither lateralized nor distinguished from their opposite hemisphere homologs in their magnitudes. The consistent differences between regional blood flow values and their corresponding regression coefficients in predicting performance suggests the presence of functional meta-networks that orchestrate the contributions of specific brain regions in support of mental and behavioral functions.

Genotypic Differences in Networks Supporting Regional Predictors of Speech Rate in Spinocerebellar Ataxia: Preliminary Observations

Background: Disordered speech production, dysarthria, is a common characteristic of the spinocerebellar ataxias (SCAs). Although dysarthric features differ across SCAs, a previous analysis revealed that a combination of regional cerebral blood flow (rCBF) in the left inferior frontal region and the right caudate predicted syllable rate, a pattern reported in normal speakers. This study examined the relationships between primary predictor brain regions and other areas of the brain in three SCA groups. The regions associated with the primary predictors are considered as elements of secondary networks since they are associated with regional speech predictors rather than directly with speech performance.

Methods: Speech and rCBF data from 9 SCA1, 8 SCA5, and 5 SCA6 individuals were analyzed. Partial correlations were used to identify brain regions associated with the primary predictors.

Results: Secondary networks differed across SCA genotypes. SCA1 and SCA6 demonstrated both positive and negative associations between primary and secondary areas, whereas the associations in the SCA5 genotype were only positive. The SCA5 associations were also largely bilaterally symmetrical. Both SCA1 and SCA5 demonstrated secondary associations with the right caudate, whereas the SCA6 group had no such associations.

Conclusions: These results demonstrate that although primary aspects of a brain network may remain functional, pathophysiological processes associated with different SCA genotypes may express themselves in alterations of broader, secondary brain networks. These secondary networks may reflect generic functional associations with the primary predictor regions, compensatory activity in the presence of an SCA, SCA pathology, or some combination of these factors.

Cortical hemodynamic mapping of subthalamic nucleus deep brain stimulation in Parkinsonian patients, using high-density functional near-infrared spectroscopy

Subthalamic nucleus deep brain stimulation (STN-DBS) is an effective treatment for idiopathic Parkinson's disease. Despite recent progress, the mechanisms responsible for the technique's effectiveness have yet to be fully elucidated. The purpose of the present study was to gain new insights into the interactions between STN-DBS and cortical network activity. We therefore combined high-resolution functional near-infrared spectroscopy with low-resolution electroencephalography in seven Parkinsonian patients on STN-DBS, and measured cortical haemodynamic changes at rest and during hand movement in the presence and absence of stimulation (the ON-stim and OFF-stim conditions, respectively) in the off-drug condition. The relative changes in oxyhaemoglobin [HbO], deoxyhaemoglobin [HbR], and total haemoglobin [HbT] levels were analyzed continuously. At rest, the [HbO], [HbR], and [HbT] over the bilateral sensorimotor (SM), premotor (PM) and dorsolateral prefrontal (DLPF) cortices decreased steadily throughout the duration of stimulation, relative to the OFF-stim condition. During hand movement in the OFF-stim condition, [HbO] increased and [HbR] decreased concomitantly over the contralateral SM cortex (as a result of neurovascular coupling), and [HbO], [HbR], and [HbT] increased concomitantly in the dorsolateral prefrontal cortex (DLPFC)-suggesting an increase in blood volume in this brain area. During hand movement with STN-DBS, the increase in [HbO] was over the contralateral SM and PM cortices was significantly lower than in the OFF-stim condition, as was the decrease in [HbO] and [HbT] in the DLPFC. Our results indicate that STN-DBS is associated with a reduction in blood volume over the SM, PM and DLPF cortices, regardless of whether or not the patient is performing a task. This particular effect on cortical networks might explain not only STN-DBS's clinical effectiveness but also some of the associated adverse effects.

Effect of Paired Associative Stimulation on Corticomotor Excitability in Chronic Smokers

Chronic smoking has been shown to have deleterious effects on brain function and is an important risk factor for ischemic stroke. Reduced cortical excitability has been shown among chronic smokers compared with non-smokers to have a long-term effect and so far no study has assessed the effect of smoking on short-term motor learning. Paired associative stimulation (PAS) is a commonly used method for inducing changes in excitability of the motor cortex (M1) in a way that simulates short-term motor learning. This study employed PAS to investigate the effect of chronic cigarette smoking on plasticity of M1. Stimulator output required to elicit a motor-evoked potential (MEP) of approximately 1 mV was similar between the groups prior to PAS. MEP response to single pulse stimuli increased in the control group and remained above baseline level for at least 30 min after the intervention, but not in the smokers who showed no significant increase in MEP size. The silent period was similar between groups at all time points of the experiment. This study suggests that chronic smoking may have a negative effect on the response to PAS and infers that chronic smoking may have a deleterious effect on the adaptability of M1.

Cortical-subcortical production of formulaic language: A review of linguistic, brain disorder, and functional imaging studies leading to a production model

Formulaic language forms about one-fourth of everyday talk. Formulaic (fixed expressions) and novel (grammatical language) differ in important characteristics. The features of idioms, slang, expletives, proverbs, aphorisms, conversational speech formulas, and other fixed expressions include ranges of length, flexible cohesion, memory storage, nonliteral and situation meaning, and affective content. Neurolinguistic observations in persons with focal brain damage or progressive neurological disease suggest that producing formulaic expressions can be achieved by interactions between the right hemisphere and subcortical structures. The known functional characteristics of these structures form a compatible substrate for production of formulaic expressions. Functional imaging using a performance-based analysis supported a right hemisphere involvement in producing conversational speech formulas, while indicating that the pause fillers, uh and um, engage the left hemisphere and function like lexical items. Together these findings support a dual-process model of language, whereby formulaic and grammatical language are modulated by different cerebral structures.

Speech networks at rest and in action: interactions between functional brain networks controlling speech production

Speech production is one of the most complex human behaviors. Although brain activation during speaking has been well investigated, our understanding of interactions between the brain regions and neural networks remains scarce. We combined seed-based interregional correlation analysis with graph theoretical analysis of functional MRI data during the resting state and sentence production in healthy subjects to investigate the interface and topology of functional networks originating from the key brain regions controlling speech, i.e., the laryngeal/orofacial motor cortex, inferior frontal and superior temporal gyri, supplementary motor area, cingulate cortex, putamen, and thalamus. During both resting and speaking, the interactions between these networks were bilaterally distributed and centered on the sensorimotor brain regions. However, speech production preferentially recruited the inferior parietal lobule (IPL) and cerebellum into the large-scale network, suggesting the importance of these regions in facilitation of the transition from the resting state to speaking. Furthermore, the cerebellum (lobule VI) was the most prominent region showing functional influences on speech-network integration and segregation. Although networks were bilaterally distributed, interregional connectivity during speaking was stronger in the left vs. right hemisphere, which may have underlined a more homogeneous overlap between the examined networks in the left hemisphere. Among these, the laryngeal motor cortex (LMC) established a core network that fully overlapped with all other speech-related networks, determining the extent of network interactions. Our data demonstrate complex interactions of large-scale brain networks controlling speech production and point to the critical role of the LMC, IPL, and cerebellum in the formation of speech production network.

Functional connectivity associated with acoustic stability during vowel production: implications for vocal-motor control

Vowels provide the acoustic foundation of communication through speech and song, but little is known about how the brain orchestrates their production. Positron emission tomography was used to study regional cerebral blood flow (rCBF) during sustained production of the vowel /a/. Acoustic and blood flow data from 13, normal, right-handed, native speakers of American English were analyzed to identify CBF patterns that predicted the stability of the first and second formants of this vowel. Formants are bands of resonance frequencies that provide vowel identity and contribute to voice quality. The results indicated that formant stability was directly associated with blood flow increases and decreases in both left- and right-sided brain regions. Secondary brain regions (those associated with the regions predicting formant stability) were more likely to have an indirect negative relationship with first formant variability, but an indirect positive relationship with second formant variability. These results are not definitive maps of vowel production, but they do suggest that the level of motor control necessary to produce stable vowels is reflected in the complexity of an underlying neural system. These results also extend a systems approach to functional image analysis, previously applied to normal and ataxic speech rate that is solely based on identifying patterns of brain activity associated with specific performance measures. Understanding the complex relationships between multiple brain regions and the acoustic characteristics of vocal stability may provide insight into the pathophysiology of the dysarthrias, vocal disorders, and other speech changes in neurological and psychiatric disorders.

Regional brain activity change predicts responsiveness to treatment for stuttering in adults

Developmental stuttering is known to be associated with aberrant brain activity, but there is no evidence that this knowledge has benefited stuttering treatment. This study investigated whether brain activity could predict progress during stuttering treatment for 21 dextral adults who stutter (AWS). They received one of two treatment programs that included periodic H2(15)O PET scanning (during oral reading, monologue, and eyes-closed rest conditions). All participants successfully completed an initial treatment phase and then entered a phase designed to transfer treatment gains; 9/21 failed to complete this latter phase. The 12 pass and 9 fail participants were similar on speech and neural system variables before treatment, and similar in speech performance after the initial phase of their treatment. At the end of the initial treatment phase, however, decreased activation within a single region, L. putamen, in all 3 scanning conditions was highly predictive of successful treatment progress.

Escitalopram Decreases Cross-Regional Functional Connectivity within the Default-Mode Network

The default-mode network (DMN), which comprises medial frontal, temporal and parietal regions, is part of the brain’s intrinsic organization. The serotonergic (5-HT) neurotransmitter system projects to DMN regions from midbrain efferents, and manipulation of this system could thus reveal insights into the neurobiological mechanisms of DMN functioning. Here, we investigate intrinsic functional connectivity of the DMN as a function of activity of the serotonergic system, through the administration of the selective serotonin reuptake inhibitor (SSRI) escitalopram. We quantified DMN functional connectivity using an approach based on dual-regression. Specifically, we decomposed group data of a subset of the functional time series using spatial independent component analysis, and projected the group spatial modes to the same and an independent resting state time series of individual participants. We found no effects of escitalopram on global functional connectivity of the DMN at the map-level; that is, escitalopram did not alter the global functional architecture of the DMN. However, we found that escitalopram decreased DMN regional pairwise connectivity, which included anterior and posterior cingulate cortex, hippocampal complex and lateral parietal regions. Further, regional DMN connectivity covaried with alertness ratings across participants. Our findings show that escitalopram altered intrinsic regional DMN connectivity, which suggests that the serotonergic system plays an important role in DMN connectivity and its contribution to cognition. Pharmacological challenge designs may be a useful addition to resting-state functional MRI to investigate intrinsic brain functional organization.

Performance-based connectivity analysis: a path to convergence with clinical studies

Connectivity analyses have become increasingly important in functional imaging. When used to describe the functional anatomy of a specific behavior, these analyses are generally applied to a subset of the data that demonstrate significant differences when experimental conditions are contrasted. Such data reduction is sub-optimal for a systems approach as it assumes that all data that survive the statistical contrast filter are related to the behavior and that none of the filtered data has a significant function. When such data filtering is applied to speech and language tasks, the resulting functional anatomy rarely reflects the brain lateralization established in over a century and a half of clinical studies. A two-step performance-based connectivity analysis is described in which the first step uses multiple linear regression to establish a direct relationship between regional brain activity and a measure of performance. The second step uses partial correlations to examine the functional relationships between the predictor regions and other brain regions. When applied to regional cerebral blood flow data obtained with positron emission tomography during a speech production task, the results demonstrate left lateralization of motor control areas, thalamic involvement in repetition rate, and auditory cortical suppression, all consistent with clinical observations. The integration of performance measures into the earliest stages of image analysis without reliance on data filtering based on decomposition may provide a path toward convergence with traditional descriptions of functional anatomy based on clinical studies.

Longitudinal cerebral blood flow changes during speech in hereditary ataxia

The hereditary ataxias constitute a group of degenerative diseases that progress over years or decades. With principal pathology involving the cerebellum, dysarthria is an early feature of many of the ataxias. Positron emission tomography was used to study regional cerebral blood flow changes during speech production over a 21 month period in a group of seven right-handed subjects with hereditary ataxia (6 females and 1 male, 3 SCA1 and 4 SCA5, aged 38.3+/-18.9 years). The decline in blood flow was greatest in cerebellar regions. In contrast, blood flow actually increased during speech production in the classic speech area (Broca's area) but not in its right-hemisphere homologue at the second evaluation. This increase in cortical flow may have been compensatory for cerebellar degeneration as speech intelligibility did not decline significantly during this period. Compensation was not complete, though, as syllable timing shifted in the direction of equal syllable duration, one of the characteristics of ataxic dysarthria. These results are consistent with previous functional imaging studies of ataxia demonstrating a pattern of brain activity that reflects both loss of function and relative compensation when clinical signs and symptoms are still mild. The combination of disease-relevant tasks, behavioral measurement, and functional imaging may provide insight into the early changes associated with neurodegenerative disease.

Regional cerebral blood flow increases during wakeful rest following cognitive training

Positron tomography was used to investigate modulations of brain activity during the so-called resting state that may occur due to a concurrent cognitive training. Twelve subjects were repeatedly scanned during resting periods and while solving logical problems containing a bias causing them to make reasoning errors. At experiment mid-time, eight subjects were trained to inhibit the reasoning bias so that their performance in solving logical problems dramatically increased afterwards, while the other four subjects were trained to logical reasoning only which did not help improving their performance. In the subgroup of subjects who increased their performance after training, we found that during the post-training resting periods, as compared to pre-training resting periods, brain activity increases in areas not belonging to the classical resting network, namely the midbrain, thalamus, peristriate, inferior frontal, and ventromedial prefrontal cortices. Strikingly, in this subgroup of subjects, these same areas were found to be also more active during post-training successful execution of the logical task, as compared to pre-training erroneous execution of the task. Such findings were not observed in the subgroup of subjects who did not improve their performance after training to logic only. These results indicate that the brain default mode is a dynamic state during which context dependent local increases of cerebral blood flow may occur on a short-term, likely for the consolidation of newly acquired knowledge.

Task-dependent organization of brain regions active during rest

The human brain demonstrates complex yet systematic patterns of neural activity at rest. We examined whether functional connectivity among those brain regions typically active during rest depends on ongoing and recent task demands and individual differences. We probed the temporal coordination among these regions during periods of language comprehension and during the rest periods that followed comprehension. Our findings show that the topography of this "rest network" varies with exogenous processing demands. The network encompassed more highly interconnected regions during rest than during listening, but also when listening to unsurprising vs. surprising information. Furthermore, connectivity patterns during rest varied as a function of recent listening experience. Individual variability in connectivity strength was associated with cognitive function: more attentive comprehenders demonstrated weaker connectivity during language comprehension, and a greater differentiation between connectivity during comprehension and rest. The regions we examined have generally been thought to form an invariant physiological and functional network whose activity reflects spontaneous cognitive processes. Our findings suggest that their function extends beyond the mediation of unconstrained thought, and that they play an important role in higher-level cognitive function.

Long-term motor training induced changes in regional cerebral blood flow in both task and resting states

Neuroimaging studies of functional activation often only reflect differentiated involvement of brain regions compared between task performance and control states. Signals common for both states are typically not revealed. Previous motor learning studies have shown that extensive motor skill training can induce profound changes in regional activity in both task and control states. To address the issue of brain activity changes in the resting-state, we explored long-term motor training induced neuronal and physiological changes in normal human subjects using functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). Ten healthy subjects performed a finger movement task daily for four weeks, during which three sessions of fMRI images and two sessions of PET images were acquired. Using a classical data analysis strategy, we found that the brain activation increased first and then returned to the pre-training, replicating previous findings. Interestingly, we also observed that motor skill training induced significant increases in regional cerebral blood flow (rCBF) in both task and resting states as the practice progressed. The apparent decrease in activation may actually result from a greater increase in activity in the resting state, rather than a decrease in the task state. By showing that training can affect the resting state, our findings have profound implications for the interpretation of functional activations in neuroimaging studies. Combining changes in resting state with activation data should greatly enhance our understanding of the mechanisms of motor-skill learning.

Does functional neuroimaging solve the questions of neurolinguistics?

Neurolinguistic research has been engaged in evaluating models of language using measures from brain structure and function, and/or in investigating brain structure and function with respect to language representation using proposed models of language. While the aphasiological strategy, which classifies aphasias based on performance modality and a few linguistic variables, has been the most stable, cognitive neurolinguistics has had less success in reliably associating more elaborately proposed levels and units of language models with brain structure. Functional imaging emerged at this stage of neurolinguistic research. In this review article, it is proposed that the often-inconsistent superfluity of outcomes arising from functional imaging studies of language awaits adjustment at both "ends" of the process: model and data. Assumptions that our current language models consistently and reliably represent implicit knowledge within human cerebral processing are in line for major revision; and the promise of functional brain imaging to reveal any such knowledge structures must incorporate stable correlates of the imaging signal as dependent variable.

How to see what you are looking for in fMRI and PET--or the crucial baseline condition

The identification of a baseline or control state is fundamental for the interpretation of task- or stimulation-induced brain activation patterns. The conscious resting state in darkness is a frequently used, but ill-defined mental state. The mere transition from, for example, lid closed to lid open in darkness causes major changes in brain activity,which can mask or mimic a stimulus-dependent brain activation. Contradictory results of seemingly identical brain activation studies may be attributed to the choice of different baseline conditions. Therefore, control conditions that are closest to the stimulus or task condition should be used as baseline in most fMRI and PET studies rather than absolute relaxation in darkness and silence (REST).

Mapping cerebral blood flow during speech production in hereditary ataxia

Dysarthria is a significant feature of the dominantly inherited spinocerebellar ataxias (SCA), but little is known about the patterns of brain activity associated with this disorder of motor speech control. Positron emission tomography (PET) was used to study regional cerebral blood flow during speech and rest in a group of 24 subjects with hereditary ataxia with mild-to-moderate dysarthria. These data were compared to the results obtained from a group of 13 age-matched, normal speakers. In the ataxic subjects, speech rates during scanning were significantly slowed compared to normal speakers. Significant reductions in mean regional blood flow were found in the cerebellum but not in supratentorial regions in the ataxic subjects. Multiple linear regression was used to model speech rate from regional blood flow. Four regions were identified as having significant relationships with speech rate in the model: the left inferior frontal and transverse temporal regions, and the right inferior cerebellar region and caudate nucleus. The relationship between flow and rate was positive in the inferior frontal and cerebellar regions and negative in the caudate and the transverse temporal region. The ataxic model represents an elaboration of the relationship previously reported for normal speakers, likely reflecting both the effects of, and compensation for, cerebellar degeneration in motor speech control. Although the mean regional blood flow values presented a pattern of functional organization for motor speech control at odds with lesion data, the performance-based model was in agreement with clinical experience. Incorporating performance data in functional image analysis may be more revealing of system characteristics than simply examining mean blood flow values.

Effects of baseline task position on apparent activation in functional imaging of memory

Brain activation dissociates during the repeated performance of memory tasks with decreasing medial temporal and increasing orbitofrontal activation. The impact of such adaptations on a baseline task is unknown. In this study, we used H2(15)O positron emission tomography (PET) in two groups of subjects performing a continuous recognition task and a baseline task. The group performing the baseline task after the main task showed significant medial temporal activation in the subtraction (recognition task-baseline). The group performing the baseline task at the beginning showed right orbitofrontal activation. These differences appeared to result primarily from different activations during the baseline task. It thus appears that the temporal context of a baseline task may fundamentally alter cognitive requirements and substantially influence apparent brain activation during a memory task. We suggest that the automatic filtration of memories according to their relevance for ongoing reality, a capacity mediated by the orbitofrontal cortex, is one such influence on apparent activation.