Multi-Level Processes and Retina–Brain Pathways of Photic Regulation of Mood

Light exerts powerful biological effects on mood regulation. Whereas the source of photic information affecting mood is well established at least via intrinsically photosensitive retinal ganglion cells (ipRGCs) secreting the melanopsin photopigment, the precise circuits that mediate the impact of light on depressive behaviors are not well understood. This review proposes two distinct retina–brain pathways of light effects on mood: (i) a suprachiasmatic nucleus (SCN)-dependent pathway with light effect on mood via the synchronization of biological rhythms, and (ii) a SCN-independent pathway with light effects on mood through modulation of the homeostatic process of sleep, alertness and emotion regulation: (1) light directly inhibits brain areas promoting sleep such as the ventrolateral preoptic nucleus (VLPO), and activates numerous brain areas involved in alertness such as, monoaminergic areas, thalamic regions and hypothalamic regions including orexin areas; (2) moreover, light seems to modulate mood through orexin-, serotonin- and dopamine-dependent pathways; (3) in addition, light activates brain emotional processing areas including the amygdala, the nucleus accumbens, the perihabenular nucleus, the left hippocampus and pathways such as the retina–ventral lateral geniculate nucleus and intergeniculate leaflet–lateral habenula pathway. This work synthetizes new insights into the neural basis required for light influence mood

Caudal inferior parietal cortex supports the hypothesis about a modulating cortical area

The cytoarchitectonically tripartite organization of the inferior parietal cortex (IPC) into the rostral, the middle and the caudal clusters has been generally ignored when associating different functions to this part of the cortex, resulting in inconsistencies about how IPC is understood. In this study, we investigated the patterns of functional connectivity of the caudal IPC in a task requiring cognitive control of language, using multiband EPI. This part of the cortex demonstrated functional connectivity patterns dissimilar to a cognitive control area and at the same time the caudal IPC showed negative functional associations with both task-related brain areas and the precuneus cortex, which is active during resting state. We found evidence suggesting that the traditional categorization of different brain areas into either task-related or resting state-related networks cannot accommodate the functions of the caudal IPC. This underlies the hypothesis about a modulating cortical area proposing that its involvement in task performance, in a modulating manner, is marked by deactivation in the patterns of functional associations with parts of the brain that are recognized to be involved in doing a task, proportionate to task difficulty; however, their patterns of functional connectivity in some other respects do not correspond to the resting state-related parts of the cortex.

Dependence of Working Memory on Coordinated Activity Across Brain Areas

Neural signatures of working memory (WM) have been reported in numerous brain areas, suggesting a distributed neural substrate for memory maintenance. In the current manuscript we provide an updated review of the literature focusing on intracranial neurophysiological recordings during WM in primates. Such signatures of WM include changes in firing rate or local oscillatory power within an area, along with measures of coordinated activity between areas based on synchronization between oscillations. In comparing the ability of various neural signatures in any brain area to predict behavioral performance, we observe that synchrony between areas is more frequently and robustly correlated with WM performance than any of the within-area neural signatures. We further review the evidence for alteration of inter-areal synchrony in brain disorders, consistent with an important role for such synchrony during behavior. Additionally, results of causal studies indicate that manipulating synchrony across areas is especially effective at influencing WM task performance. Each of these lines of research supports the critical role of inter-areal synchrony in WM. Finally, we propose a framework for interactions between prefrontal and sensory areas during WM, incorporating a range of experimental findings and offering an explanation for the observed link between intra-areal measures and WM performance.

Region Specificity in Endogenous Opioid Peptides and Mu-opioid Receptor Gene Expression in Rat Brain Areas Involved in Addiction After Frequent Morphine Treatment

Backgrounds: Molecular mechanisms involved in adverse effects of morphine, including tolerance and dependence, have remained elusive. We examined possible alterations in the gene expression of proenkephalin (Penk), prodynorphin (Pdyn), and mu-opioid receptor (Oprm1) in reward brain areas following frequent morphine treatment. Methods: Two groups of male Wistar rats were used. The groups received either saline (1 mL/kg) or morphine (10 mg/kg) twice daily for eight days. On day 8, rats were decapitated, brain areas involved in addiction were dissected, including the midbrain, striatum, prefrontal cortex (PFC), hippocampus, and hypothalamus, and gene expression was evaluated with real-time PCR. Results: Prolonged morphine treatment decreased Penk, Pdyn, and Oprm1 gene expressions in the midbrain but upregulated them in the striatum compared to the control group treated with saline. Significant increases in Pdyn and Oprm1 gene expressions were detected in the PFC, but there was no significant difference in Penk gene expression between the two groups. Besides, Pdyn gene expression was decreased in the hippocampus and hypothalamus; however, no significant differences in Penk and Oprm1 gene expressions were detected between the groups in these areas. Conclusions: The expression of endogenous opioid peptides and receptors after frequent use of morphine follows a region specificity in brain areas involved in addiction. These alterations may result in new physiological setpoints outside the normal range, which need to be considered when using morphine in medicine.

ECG monitoring of post-stroke occurring arrhythmias: an observational study using 7-day Holter ECG

Post-stroke arrhythmias represent a risk factor for complications and worse prognosis after cerebrovascular events. The aims of the study were to detect the rate of atrial fibrillation (AF) and other cardiac arrhythmias after acute ischemic stroke, by using a 7-day Holter ECG which has proved to be superior to the standard 24-h recording, and to evaluate the possible association between brain lesions and arrhythmias. One hundred and twenty patients with cryptogenic ischemic stroke underwent clinical and neuroimaging assessment and were monitored with a 7-day Holter ECG. Analysis of the rhythm recorded over 7 days was compared to analysis limited at the first 24 h of monitoring. 7-day Holter ECG detected AF in 4% of patients, supraventricular extrasystole (SVEB) in 94%, ventricular extrasystole (VEB) in 88%, short supraventricular runs (SVRs) in 54%, supraventricular tachycardia in 20%, and bradycardia in 6%. Compared to the first 24 h of monitoring, 7-Holter ECG showed a significant higher detection for all arrhythmias (AF p = 0.02; bradycardia p = 0.03; tachycardia p = 0.0001; SVEB p = 0.0002; VEB p = 0.0001; SVRs p = 0.0001). Patients with SVRs and bradycardia were older (p = 0.0001; p = 0.035) and had higher CHA2DS2VASc scores (p = 0.004; p = 0.026) respectively, in the comparison with patients without these two arrhythmias. An association was found between SVEB and parietal (p = 0.013) and temporal (p = 0.013) lobe lesions, whereas VEB correlated with insular involvement (p = 0.002). 7-day Holter ECG monitoring proved to be superior as compared to 24-h recording for the detection of all arrhythmias, some of which (SVEB and VEB) were associated with specific brain areas involvement. Therefore, 7-day Holter ECG should be required as an effective first-line approach to improve both diagnosis and therapeutic management after stroke.

Synchronization in the connectome: Metastable oscillatory modes emerge from interactions in the brain spacetime network

A rich repertoire of oscillatory signals is detected from human brains with electro- and magnetoencephalography (EEG/MEG). However, the principles underwriting coherent oscillations and their link with neural activity remain unclear. Here, we hypothesise that the emergence of transient brain rhythms is a signature of weakly stable synchronization between spatially distributed brain areas, occurring at network-specific collective frequencies due to non-negligible conduction times. We test this hypothesis using a phenomenological network model to simulate interactions between neural mass potentials (resonating at 40Hz) in the structural connectome. Crucially, we identify a critical regime where metastable oscillatory modes emerge spontaneously in the delta (0.5-4Hz), theta (4-8Hz), alpha (8-13Hz) and beta (13-30Hz) frequency bands from weak synchronization of subsystems, closely approximating the MEG power spectra from 89 healthy individuals. Grounded in the physics of delay-coupled oscillators, these numerical analyses demonstrate the role of the spatiotemporal connectome in structuring brain activity in the frequency domain.

Dysregulation of GABAergic Signaling in Neurodevelomental Disorders: Targeting Cation-Chloride Co-transporters to Re-establish a Proper E/I Balance

The construction of the brain relies on a series of well-defined genetically and experience- or activity -dependent mechanisms which allow to adapt to the external environment. Disruption of these processes leads to neurological and psychiatric disorders, which in many cases are manifest already early in postnatal life. GABA, the main inhibitory neurotransmitter in the adult brain is one of the major players in the early assembly and formation of neuronal circuits. In the prenatal and immediate postnatal period GABA, acting on GABAA receptors, depolarizes and excites targeted cells via an outwardly directed flux of chloride. In this way it activates NMDA receptors and voltage-dependent calcium channels contributing, through intracellular calcium rise, to shape neuronal activity and to establish, through the formation of new synapses and elimination of others, adult neuronal circuits. The direction of GABAA-mediated neurotransmission (depolarizing or hyperpolarizing) depends on the intracellular levels of chloride [Cl−]i, which in turn are maintained by the activity of the cation-chloride importer and exporter KCC2 and NKCC1, respectively. Thus, the premature hyperpolarizing action of GABA or its persistent depolarizing effect beyond the postnatal period, leads to behavioral deficits associated with morphological alterations and an excitatory (E)/inhibitory (I) imbalance in selective brain areas. The aim of this review is to summarize recent data concerning the functional role of GABAergic transmission in building up and refining neuronal circuits early in development and its dysfunction in neurodevelopmental disorders such as Autism Spectrum Disorders (ASDs), schizophrenia and epilepsy. In particular, we focus on novel information concerning the mechanisms by which alterations in cation-chloride co-transporters (CCC) generate behavioral and cognitive impairment in these diseases. We discuss also the possibility to re-establish a proper GABAA-mediated neurotransmission and excitatory (E)/inhibitory (I) balance within selective brain areas acting on CCC.

Are Older Adults’ Difficulties on Emotion Recognition and Theory of Mind Tasks Due to a Decline in General Cognitive Ability?

Older adults have both worse general cognition and worse social cognition. A frequent suggestion is that worse social cognition is due to worse general cognition. However, previous studies have often provided contradictory evidence. The current study examined this issue with a more extensive battery of tasks for both forms of cognition. We gave 47 young and 40 older adults three tasks to assess general cognition (processing speed, working memory, fluid intelligence) and three tasks to assess their social cognition (emotion and theory-of-mind). Older adults did worse on all tasks and there were correlations between general and social cognition. Although working memory and fluid intelligence were unique predictors of performance on the Emotion Photos task and the Eyes task, Age Group was a unique predictor on all three social cognitiaon tasks. Thus, there were relations between the two forms of cognition but older adults continued to do worse than young adults even after accounting for general cognition. We argue that this pattern of results is due to some overlap in brain areas mediating general and social cognition, but also independence, and with a differential rate of decline in brain areas dedicated to general cognition versus social cognition.

Beyond “Sex Prediction”: Estimating and Interpreting Multivariate Sex Differences and Similarities in the Brain

Previous studies have shown that machine-learning (ML) algorithms can “predict” sex based on brain anatomical/ functional features. The high classification accuracy achieved by ML algorithms is often interpreted as revealing large differences between the brains of males and females and as confirming the existence of “male/female brains”. However, classification and estimation are quite different concepts, and using classification metrics as surrogate estimates of between-group differences results in major statistical and interpretative distortions. The present study illustrates these distortions and provides a novel and detailed assessment of multivariate sex differences in gray matter volume (GMVOL) that does not rely on classification metrics. Moreover, modeling and clustering techniques and analyses of similarities (ANOSIM) were used to identify the brain areas that contribute the most to these multivariate differences, and to empirically assess whether they assemble into two sex-typical profiles. Results revealed that multivariate sex differences in GMVOL: 1) are “large” if not adjusted for total intracranial volume (TIV) variation, but “small” when controlling for this variable; 2) differ in size between individuals and also depends on the ML algorithm used for their calculation 3) do not stem from two sex-typical profiles, and so describing them in terms of “male/female brains” is misleading.