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Better understanding of breathlessness perception addresses an unmet clinical need for more effective treatments for intractable dyspnoea, a prevalent symptom of multiple medical conditions. The insular-cortex is predominantly activated in brain-imaging studies of dyspnoea, but its precise role remains unclear. We measured experimentally-induced hypercapnic air-hunger in three insular-glioma patients before and after surgical resection. Tests involved one-minute increments in inspired CO2, raising end-tidal PCO2 to 7.5 mmHg above baseline (38.5 ± 5.7 mmHg), whilst ventilation was constrained (10.7 ± 2.3 L/min). Patients rated air-hunger on a visual analogue scale (VAS). Patients had lower stimulus–response (2.8 ± 2 vs. 11 ± 4 %VAS/mmHg; p = 0.004), but similar threshold (40.5 ± 3.9 vs. 43.2 ± 5.1 mmHg), compared to healthy individuals. Volunteered comments implicated diminished affective valence. After surgical resection; sensitivity increased in one patient, decreased in another, and other was unable to tolerate the ventilatory limit before any increase in inspired CO2.We suggest that functional insular-cortex is essential to register breathlessness unpleasantness and could be targeted with neuromodulation in chronically-breathless patients. Neurological patients with insula involvement should be monitored for blunted breathlessness to inform clinical management.

BackgroundDeep brain stimulation (DBS) has shown promise in effectively treating chronic pain. This study aimed to assess the efficacy of DBS in this context.MethodsWe conducted a systematic literature search using PubMed, Scopus, and Web of Science, following the PRISMA guidelines. A well-constructed search strategy was utilized. Our literature search identified two groups of subjects: one group underwent DBS specifically for chronic pain treatment (DBS-P), while the second group received DBS for other indications (DBS-O), such as Parkinson’s disease or dystonia, with pain perception investigated as a secondary outcome in this population. Meta-analysis was performed using R version 4.2.3 software. Heterogeneity was assessed using the tau^2 and I^2 indices, and Cochran’s Q-test was conducted.ResultsThe analysis included 966 patients in 43 original research studies with chronic pain who underwent DBS (340 for DBS-P and 625 for DBS-O). Subgroup analysis revealed that DBS-P exhibited a significant effect on chronic pain relief, with a standardized mean difference (SMD) of 1.65 and a 95% confidence interval (CI) of [1.31; 2.00]. Significant heterogeneity was observed among the studies, with an I^2 value of 85.8%. However, no significant difference was found between DBS-P and DBS-O subgroups. Subgroup analyses based on study design, age, pain diseases, and brain targets demonstrated varying levels of evidence for the effectiveness of DBS across different subgroups. Additionally, meta-regression analyses showed no significant relationship between age or pain duration and DBS effectiveness for chronic pain.ConclusionThese findings significantly contribute to the expanding body of knowledge regarding the utility of DBS in the management of chronic pain. The study underscores the importance of conducting further research to enhance treatment outcomes and elucidate patient-specific factors that are associated with treatment response.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=428442, identifier CRD42023428442.

IntroductionAnorexia nervosa (AN) is one of the most debilitating psychiatric disorders, becoming severe and enduring in a third of cases; with few effective treatments. Deep brain stimulation is a reversible, adjustable neurosurgical procedure that has been gaining ground in psychiatry as a treatment for depression and obsessive–compulsive disorder, yet few studies have investigated AN. Abnormal eating behavior and the compulsive pursuit of thinness in AN is, in part, a consequence of dysfunction in reward circuitry and the nucleus accumbens (NAcc) is central to reward processing.MethodsPhase 1 prospective open-label pilot study of seven individuals with severe enduring AN. Electrodes were implanted bilaterally into the NAcc with stimulation at the anterior limb of the internal capsule using rechargeable implantable pulse generators. The protocol of 15 months included 12 months of deep brain stimulation incorporating two consecutive, randomized blind on-off fortnights 9 months after stimulation onset. The primary objectives were to investigate safety and feasibility, together with changes in eating disorder psychopathology.ResultsFeasibility and safety was demonstrated with no serious adverse events due to deep brain stimulation. Three patients responded to treatment [defined as > 35% reduction in Eating Disorders Examination (EDE) score at 12 months] and four patients were non-responders. Responders had a statistically significant mean reduction in EDE scores (50.3% reduction; 95% CI 2.6–98.2%), Clinical Impairment Assessment (45.6% reduction; 95% CI 7.4–83.7%). Responders also had a statistically significant mean reduction in Hamilton Depression Scale, Hamilton Anxiety Scale and Snaith-Hamilton pleasure scale. There were no statistically significant changes in Body Mass Index, Yale-Brown-Cornell Eating Disorder Scale, Yale-Brown Obsessive–Compulsive Scale and World Health Organization Quality of Life Psychological subscale.ConclusionThis study provides some preliminary indication that deep brain stimulation to the NAcc. Might potentially improve some key features of enduring AN. In this small study, the three responders had comorbid obsessive-compulsive disorder which predated AN diagnosis. Future studies should aim to further elucidate predictors of outcome.Clinical Trial Registration[www.ClinicalTrials.gov], identifier [Project ID 128658].

The dorsal anterior cingulate cortex (dACC) is a key node in the human salience network. It has been ascribed motor, pain-processing and affective functions. However, the dynamics of information flow in this complex region and how it responds to inputs remain unclear and are difficult to study using non-invasive electrophysiology. The area is targeted by neurosurgery to treat neuropathic pain. During deep brain stimulation surgery, we recorded local field potentials from this region in humans during a decision-making task requiring motor output. We investigated the spatial and temporal distribution of information flow within the dACC. We demonstrate the existence of a distributed network within the anterior cingulate cortex where discrete nodes demonstrate directed communication following inputs. We show that this network anticipates and responds to the valence of feedback to actions. We further show that these network dynamics adapt following learning. Our results provide evidence for the integration of learning and the response to feedback in a key cognitive region.

The autonomic nervous system (ANS) is involved in the regulation of physiologic and homeostatic parameters relating particularly to the visceral organs and the co-ordination of physiological responses to threat. Blood pressure and heart rate, respiration, pupillomotor reactivity, sexual function, gastrointestinal secretions and motility, and urine storage and micturition are all under a degree of ANS control. Furthermore, there is close integration between the ANS and other neural functions such as emotion and cognition, and thus brain regions that are known to be important for autonomic control are also implicated in emotional functions. In this review we explore the role of the central ANS in the control of the bladder, and the implications of this for bladder dysfunction in diseases of the ANS.

The dorsal anterior cingulate cortex (dACC) is proposed to facilitate learning by signaling mismatches between the expected outcome of decisions and the actual outcomes in the form of prediction errors. The dACC is also proposed to discriminate outcome valence—whether a result has positive (either expected or desirable) or negative (either unexpected or undesirable) value. However, direct electrophysiological recordings from human dACC to validate these separate, but integrated, dimensions have not been previously performed. We hypothesized that local field potentials (LFPs) would reveal changes in the dACC related to prediction error and valence and used the unique opportunity offered by deep brain stimulation (DBS) surgery in the dACC of three human subjects to test this hypothesis. We used a cognitive task that involved the presentation of object pairs, a motor response, and audiovisual feedback to guide future object selection choices. The dACC displayed distinctly lateralized theta frequency (3–8 Hz) event-related potential responses—the left hemisphere dACC signaled outcome valence and prediction errors while the right hemisphere dACC was involved in prediction formation. Multivariate analyses provided evidence that the human dACC response to decision outcomes reflects two spatiotemporally distinct early and late systems that are consistent with both our lateralized electrophysiological results and the involvement of the theta frequency oscillatory activity in dACC cognitive processing. Further findings suggested that dACC does not respond to other phases of action-outcome-feedback tasks such as the motor response which supports the notion that dACC primarily signals information that is crucial for behavioral monitoring and not for motor control.

In neuropathic pain, the neurophysiological and neuropathological function of the ventro-posterolateral nucleus of the thalamus (VPL) and the periventricular gray/periaqueductal gray area (PVAG) involves multiple frequency oscillations. Moreover, oscillations related to pain perception and modulation change dynamically over time. Fluctuations in these neural oscillations reflect the dynamic neural states of the nucleus. In this study, an approach to classifying the synchronization level was developed to dynamically identify the neural states. An oscillation extraction model based on windowed wavelet packet transform was designed to characterize the activity level of oscillations. The wavelet packet coefficients sparsely represented the activity level of theta and alpha oscillations in local field potentials (LFPs). Then, a state discrimination model was designed to calculate an adaptive threshold to determine the activity level of oscillations. Finally, the neural state was represented by the activity levels of both theta and alpha oscillations. The relationship between neural states and pain relief was further evaluated. The performance of the state identification approach achieved sensitivity and specificity beyond 80% in simulation signals. Neural states of the PVAG and VPL were dynamically identified from LFPs of neuropathic pain patients. The occurrence of neural states based on theta and alpha oscillations were correlated to the degree of pain relief by deep brain stimulation. In the PVAG LFPs, the occurrence of the state with high activity levels of theta oscillations independent of alpha and the state with low-level alpha and high-level theta oscillations were significantly correlated with pain relief by deep brain stimulation. This study provides a reliable approach to identifying the dynamic neural states in LFPs with a low signal-to-noise ratio by using sparse representation based on wavelet packet transform. Furthermore, it may advance closed-loop deep brain stimulation based on neural states integrating multiple neural oscillations.

It is unclear whether Hebbian-like learning occurs at the level of long-range white matter connections in humans, i.e. where measurable changes in structural connectivity are correlated with changes in functional connectivity. However, the behavioral changes observed after deep brain stimulation (DBS) suggest the existence of such Hebbian-like mechanisms occurring at the structural level with functional consequences. In this rare case study, we obtained the full network of white matter connections of one patient with Parkinson's disease before and after long-term DBS and combined it with a computational model of ongoing activity to investigate the effects of DBS-induced long-term structural changes. The results show that the long-term effects of DBS on resting-state functional connectivity is best obtained in the computational model by changing the structural weights from the subthalamic nucleus to the putamen and the thalamus in a Hebbian-like manner. Moreover, long-term DBS also significantly changed the structural connectivity towards normality in terms of model-based measures of segregation and integration of information processing, two key concepts of brain organization. This novel approach using computational models to model the effects of Hebbian-like changes in structural connectivity allowed us to causally identify the possible underlying neural mechanisms of long-term DBS using rare case study data. In time, this could help predict the efficacy of individual DBS targeting and identify novel DBS targets.