Sublexical cues affect degraded speech processing: insights from fMRI.

In natural listening situations, speech perception is often impaired by degraded speech sounds arriving at the ear. Contextual speech information can improve the perception of degraded speech and modify neuronal responses elicited by degraded speech. However, most studies on context effects on neural responses to degraded speech confounded lexico-semantic and sublexical cues. Here, we used fMRI to investigate how prior sublexical speech (e.g. pseudowords cues) affects neural responses to degraded sublexical speech and hence its processing and recognition. Each trial consisted of three consecutively presented pseudowords, of which the first and third were identical and degraded. The second pseudoword was always presented in clear form and either matched or did not match the degraded pseudowords. Improved speech processing through sublexical processing was associated with BOLD activation increases in frontal, temporal, and parietal regions, including the primary auditory cortex (PAC), posterior superior temporal cortex, angular gyrus, supramarginal gyrus, middle temporal cortex, and somato-motor cortex. These brain regions are part of a speech processing network and are involved in lexico-semantic processing. To further investigate the adaptive changes in PAC, we conducted a bilateral region of interest analysis on PAC subregions. PAC ROIs showed bilaterally increased activation in the match condition compared with the mismatch condition. Our results show that the perception of unintelligible degraded speech is improved and the neuronal population response is enhanced after exposure to intact sublexical cues. Furthermore, our findings indicate that the processing of clear meaningless sublexical speech preceding degraded speech could enhance the activity in the brain regions that belong to the cortical speech processing network previously reported in studies investigating lexico-semantic speech.

Five weeks of intermittent transcutaneous vagus nerve stimulation shape neural networks: a machine learning approach.

Invasive and transcutaneous vagus nerve stimulation [(t)-VNS] have been used to treat epilepsy, depression and migraine and has also shown effects on metabolism and body weight. To what extent this treatment shapes neural networks and how such network changes might be related to treatment effects is currently unclear. Using a pre-post mixed study design, we applied either a tVNS or sham stimulation (5 h/week) in 34 overweight male participants in the context of a study designed to assess effects of tVNS on body weight and metabolic and cognitive parameters resting state (rs) fMRI was measured about 12 h after the last stimulation period. Support vector machine (SVM) classification was applied to fractional amplitude low-frequency fluctuations (fALFF) on established rs-networks. All classification results were controlled for random effects and overfitting. Finally, we calculated multiple regressions between the classification results and reported food craving. We found a classification accuracy (CA) of 79 % in a subset of four brainstem regions suggesting that tVNS leads to lasting changes in brain networks. Five of eight salience network regions yielded 76,5 % CA. Our study shows tVNS' post-stimulation effects on fALFF in the salience rs-network. More detailed investigations of this effect and their relationship with food intake seem reasonable for future studies.

Brain activations show association with subsequent endocrine responses to oral glucose challenge in a satiation-level dependent manner.

Aims: The communication between brain and peripheral homeostatic systems is a central element of ingestive control. We set out to explore which parts of the brain have strong functional connections to peripheral signalling molecules in a physiological context. It was hypothesised that associations can be found between endocrine response to glucose ingestion and preceding brain activity in dependence of the nutritional status of the body. Materials and methods: Young, healthy male participants underwent both a 38 â€‹h fasting and a control condition with standardized meals. On the second day of the experiment, participants underwent fMRI scanning followed by ingestion of glucose solution in both conditions. Subsequent endocrine responses relevant to energy metabolism were assessed. Associations between preceding brain activation and endocrine responses were examined. Results: In both fasting and non-fasting conditions, brain activity was associated with subsequent endocrine responses after glucose administration, but relevant brain areas differed substantially between the conditions. In the fasting condition relations between the caudate nucleus and the orbitofrontal regions with insulin and C-peptide were prevailing, whereas in the non-fasting condition associations between various brain regions and adiponectin and cortisol were the predominant significant outcome. Conclusion: Connections between endocrine response following a glucose challenge and prior brain activity suggests that the brain is playing an active role in the networks regulating food intake and associated endocrine signals. Further studies are needed to demonstrate causation.

Effects of hunger, satiety and oral glucose on effective connectivity between hypothalamus and insular cortex.

The hypothalamus and insular cortex play an essential role in the integration of endocrine and homeostatic signals and their impact on food intake. Resting-state functional connectivity alterations of the hypothalamus, posterior insula (PINS) and anterior insula (AINS) are modulated by metabolic states and caloric intake. Nevertheless, a deeper understanding of how these factors affect the strength of connectivity between hypothalamus, PINS and AINS is missing. This study investigated whether effective (directed) connectivity within this network varies as a function of prandial states (hunger vs. satiety) and energy availability (glucose levels and/or hormonal modulation). To address this question, we measured twenty healthy male participants of normal weight twice: once after 36 â€‹h of fasting (except water consumption) and once under satiated conditions. During each session, resting-state functional MRI (rs-fMRI) and hormone concentrations were recorded before and after glucose administration. Spectral dynamic causal modeling (spDCM) was used to assess the effective connectivity between the hypothalamus and anterior and posterior insula. Using Bayesian model selection, we observed that the same model was identified as the most likely model for each rs-fMRI recording. Compared to satiety, the hunger condition enhanced the strength of the forward connections from PINS to AINS and reduced the strength of backward connections from AINS to PINS. Furthermore, the strength of connectivity from PINS to AINS was positively related to plasma cortisol levels in the hunger condition, mainly before glucose administration. However, there was no direct relationship between glucose treatment and effective connectivity. Our findings suggest that prandial states modulate connectivity between PINS and AINS and relate to theories of interoception and homeostatic regulation that invoke hierarchical relations between posterior and anterior insula.

Endocrine profile dataset of fasting and normally eating young, healthy men and following activation of brain areas involved in ingestive behaviour.

Data includes endocrine data (adiponectin, ACTH, cortisol, C-peptide, insulin and glucose) of a 38 hour fasting intervention and a control condition with standardised meals in young healthy male subjects. The data was collected using a within-design approach. The data of ten common bilateral regions of interest (ROIs) involved in ingestive behaviour are included as fMRI percent signal change measurements of the amygdala, caudate nucleus, insula (classified into three regions), nucleus accumbens (NAcc), orbitofrontal cortex (OFC, classified into two different regions), pallidum, and lastly, the putamen. These measurements were performed whilst images of food were shown to participants during fMRI who would rate them on a scale from 1 to 8. Reaction times as well as each image's score are also included in the dataset. Endocrine data is especially useful as it is a well-controlled dataset of healthy young males in fasting and satiated conditions. Furthermore, this data can provide a physiological reference for experiments in patients with impaired glucose tolerance or metabolic syndrome. fMRI data may be useful as an extension of an existing dataset or for replication of the collected data.

Cerebello-striatal interaction mediates effects of subthalamic nucleus deep brain stimulation in Parkinson's disease.

BACKGROUND: In Parkinson's disease (PD), dopamine replacement therapy (DRT) enhances the effective connectivity of the prefrontal cortex (PFC) and supplementary motor area (SMA). The clinical effects of deep brain stimulation (DBS) of the subthalamic nucleus (STN) go beyond DRT effects including highly beneficial tremor suppression. OBJECTIVES: Here, we aimed to determine DBS-related changes of a motor network using resting state fMRI in PD patients with chronic STN DBS. METHODS: In a repeated-measurement design, 26 medicated PD patients (60.9 years (SD 8.9)) were investigated using resting state fMRI while bipolar STN stimulation was (i) active or (ii) switched off, and dynamic causal modelling was subsequently performed. RESULTS: DBS improved the MDS-UPDRS-III score by 26.4% (DBS ON/Med ON vs. DBS OFF/Med ON). Active stimulation resulted in an increased effective connectivity from cerebellum to putamen (p = 0.00118). In addition, there was a stronger coupling from PFC to cerebellum (p = 0.021), as well as from cerebellum to SMA (p = 0.043) on an uncorrected level. Coupling strength from PFC to cerebellum correlated with the DBS-related change of the resting tremor subscore (r = 0.54, p = 0.031). Self-connections increased as a function of DBS in the right PFC, PMC, SMA, M1, thalamus and left cerebellum. CONCLUSIONS: DBS-related improvement of Parkinsonian signs appears to be driven by an interaction between the cerebellum and the putamen. Resting tremor suppression may be related to an enhanced prefronto-cerebellar network. Activation of the mesial premotor loop (PFC-SMA) as seen in DRT may thus be secondary due to the primary modulation of cerebellar networks.

Modulation of brain activity by hormonal factors in the context of ingestive behaviour.

INTRODUCTION: Metabolic and hormonal signals have been shown to be associated with brain activity in the context of ingestive behaviour. However, this has mostly been seen in studies using external administration of hormones or glucose. We therefore studied endocrine-brain interaction in a physiological setting with hormone levels determined by metabolic conditions such as normal food intake vs. prolonged fasting. METHODS: 24 healthy, normal weight men participated in two sessions, one involving a 38-hour fasting period and one a non-fasting control condition with standardized meals. Functional magnetic resonance imaging was performed at the end of the experiment with participants being required to rate pictures of food. Brain activation was compared between conditions in predefined regions of interest (ROIs). Multiple blood samples were taken to determine levels of insulin, C-peptide, cortisol, ACTH, glucose and adiponectin. These were used as a predictor variable in a regression analysis on brain activations in the different ROIs. RESULTS: Food pictures were rated as more desirable in the fasting condition. Univariate analysis of ROI activations revealed mainly effects of food rating and no significant effects of the metabolic state. Multiple regression analysis revealed associations between orbitofrontal cortex activation and blood glucose in the non-fasting condition. In the fasting condition adiponectin was associated with the signal from the caudate nucleus and insulin and C-peptide were associated with functional activity of orbitofrontal regions. DISCUSSION: Associations of endocrine signals and functional neural regions could be demonstrated in a realistic setting without external administration of hormones. As the current approach was correlational, further studies need to address the causal role of hormonal signals.

Machine Learning Based Classification of Resting-State fMRI Features Exemplified by Metabolic State (Hunger/Satiety).

OBJECTIVE: Resting-state functional magnetic resonance imaging (rs-fMRI) has become an essential measure to investigate the human brain's spontaneous activity and intrinsic functional connectivity. Several studies including our own previous work have shown that the brain controls the regulation of energy expenditure and food intake behavior. Accordingly, we expected different metabolic states to influence connectivity and activity patterns in neuronal networks. METHODS: The influence of hunger and satiety on rs-fMRI was investigated using three connectivity models (local connectivity, global connectivity and amplitude rs-fMRI signals). After extracting the connectivity parameters of 90 brain regions for each model, we used sequential forward floating selection strategy in conjunction with a linear support vector machine classifier and permutation tests to reveal which connectivity model differentiates best between metabolic states (hunger vs. satiety). RESULTS: We found that the amplitude of rs-fMRI signals is slightly more precise than local and global connectivity models in order to detect resting brain changes during hunger and satiety with a classification accuracy of 81%. CONCLUSION: The amplitude of rs-fMRI signals serves as a suitable basis for machine learning based classification of brain activity. This opens up the possibility to apply this combination of algorithms to similar research questions, such as the characterization of brain states (e.g., sleep stages) or disease conditions (e.g., Alzheimer's disease, minimal cognitive impairment).

Impact of Hunger, Satiety, and Oral Glucose on the Association Between Insulin and Resting-State Human Brain Activity.

To study the interplay of metabolic state (hungry vs. satiated) and glucose administration (including hormonal modulation) on brain function, resting-state functional magnetic resonance imaging (rs-fMRI) and blood samples were obtained in 24 healthy normal-weight men in a repeated measurement design. Participants were measured twice: once after a 36 h fast (except water) and once under satiation (three meals/day for 36 h). During each session, rs-fMRI and hormone concentrations were recorded before and after a 75 g oral dose of glucose. We calculated the amplitude map from blood-oxygen-level-dependent (BOLD) signals by using the fractional amplitude of low-frequency fluctuation (fALFF) approach for each volunteer per condition. Using multiple linear regression analysis (MLRA) the interdependence of brain activity, plasma insulin and blood glucose was investigated. We observed a modulatory impact of fasting state on intrinsic brain activity in the posterior cingulate cortex (PCC). Strikingly, differences in plasma insulin levels between hunger and satiety states after glucose administration at the time of the scan were negatively related to brain activity in the posterior insula and superior frontal gyrus (SFG), while plasma glucose levels were positively associated with activity changes in the fusiform gyrus. Furthermore, we could show that changes in plasma insulin enhanced the connectivity between the posterior insula and SFG. Our results indicate that hormonal signals like insulin alleviate an acute hemostatic energy deficit by modifying the homeostatic and frontal circuitry of the human brain.

Endocrine responses and food intake in fasted individuals under the influence of glucose ingestion.

INTRODUCTION: Different metabolic conditions can affect what and how much we eat. Hormones of glucose metabolism and adipokines such as adiponectin take part in the control of these decisions and energy balance of the body. However, a comprehensive understanding of how these endocrine and metabolic factors influence food intake has not been reached. We hypothesised that the amount of food a person consumes differs substantially after a fasting period even after the energy deficit was partially removed by glucose ingestion and endocrine signals like insulin and C-peptide indicated a high glucose metabolic status. Furthermore, the macronutrient composition of the consumed food and a possible association with adiponectin under the influence of glucose ingestion was assessed. METHODS: In a within-subject design, 24 healthy males participated in both a fasting (42 h) and control (non-fasting) condition. A total of 20 blood samples from each subject were collected during each condition to assess serum levels of adiponectin, insulin, C-peptide, cortisol and ACTH. At the end of each condition food intake was measured with an ad libitum buffet after the acute energy deficit was compensated using a carbohydrate-rich drink. RESULTS: The total amount of caloric intake and single macronutrients was higher after the fasting intervention after replenishment with glucose. All recorded hormone levels, except for adiponectin, were significantly different for at least one of the study intervals. The relative proportions of the macronutrient composition of the consumed food were stable in both conditions under the influence of glucose ingestion. In the non-fasting condition, the relative amount of protein intake correlated with adiponectin levels during the experiment. DISCUSSION AND CONCLUSION: An anabolic glucose metabolism after glucose ingestion following a fasting intervention did not even out energy ingestion compared to a control group with regular food intake and glucose ingestion. Anorexigenic hormones like insulin in this context were not able despite higher levels than in the control condition to ameliorate the drive for food intake to normal or near normal levels. Relative macronutrient intake remains stable under these varying metabolic conditions and glucose influence. Serum adiponectin levels showed a positive association with the relative protein intake in the non-fasting condition under the influence of glucose although adiponectin levels overall did not differ in between the conditions.

Influences of Hunger, Satiety and Oral Glucose on Functional Brain Connectivity: A Multimethod Resting-State fMRI Study.

A major regulatory task of the organism is to keep brain functions relatively constant in spite of metabolic changes (e.g., hunger vs. satiety) or availability of energy (e.g., glucose administration). Resting-state functional magnetic resonance imaging (rs-fMRI) can reveal resulting changes in brain function but previous studies have focused mostly on the hypothalamus. Therefore, we took a whole-brain approach and examined 24 healthy normal-weight men once after 36 h of fasting and once in a satiated state (six meals over the course of 36 h). At the end of each treatment, rs-fMRI was recorded before and after the oral administration of 75 g of glucose. We calculated local connectivity (regional homogeneity [ReHo]), global connectivity (degree of centrality [DC]), and amplitude (fractional amplitude of low-frequency fluctuation [fALFF]) maps from the rs-fMRI data. We found that glucose administration reduced all measures selectively in the left supplementary motor area and increased ReHo and fALFF in the right middle and superior frontal gyri. For fALFF, we observed a significant interaction between metabolic states and glucose in the left thalamus. This interaction was driven by a fALFF increase after glucose treatment in the hunger relative to the satiety condition. Our results indicate that fALFF analysis is the most sensitive measure to detect effects of metabolic states on resting-state brain activity. Moreover, we show that multimethod rs-fMRI provides an unbiased approach to identify spontaneous brain activity associated with changes in homeostasis and caloric intake.