Neural Signatures Research Articles

Divergent patterns of cognitive deficits and structural brain alterations between older adults in mixed-sex and same-sex relationships.

BackgroundSexual minority (SM) older adults experience mental health disparities. Psychiatric disorders and neuropsychiatric symptoms (NPS) are risk factors for cognitive decline. Although older people in same-sex (SSR) compared to mixed-sex relationships (MSR) perform more poorly on cognitive screening tests, prior studies found no differences in rates of dementia diagnosis or neuropsychological profiles. We sought to explore the role of NPS on neurocognitive outcomes for SM populations. We compared cognitive performance and structural brain parameters of older adults in SSR and MSR.MethodsData were originally collected at Alzheimer's Disease Research Centers (ADRCs). Inclusion criteria were: age of 55+ years, a study partner identified as a spouse/partner, and availability of T1-MRI brain volumes/thickness. Participants were labeled as either SSR or MSR based on their/their co-participant's reported sex. We identified 1,073 participants (1,037 MSR−555 cognitively unimpaired [CU]; 36 SSR−23 CU) with structural MRI data, Mini-Mental State Exam (MMSE), and Neuropsychiatric Inventory Questionnaire (NPI-Q) scores. A subset of the overall sample completed comprehensive neuropsychological assessment (n = 939; 908 MSR−494 CU; 31 SSR−22 CU). Covariates included in statistical models were age, sex, education, total intracranial volume, and apolipoprotein E genotype.ResultsMultivariate general linear models showed significant diagnosis-by-relationship interaction effects on the left parahippocampal gyrus volume. After stratification by relationship group, only cognitively impaired (CI) MSR had significantly smaller left parahippocampal volumes than MSR-CU. The SSR group showed better episodic memory performance. Severity of neuropsychiatric symptoms was negatively associated with volume/thickness of bilateral fronto-temporal areas and with MMSE scores, predominantly in the MSR group.ConclusionIn our study, MSR participants presented with a more compromised cognitive profile than SSR participants. MSR-CI participants showed significantly smaller left medio-temporal volumes, a neural signature of AD. Neuropsychiatric symptoms predicted smaller fronto-temporal volumes in the MSR more consistently than in the SSR group. These findings may be due to unexplored protective factors against cognitive decline in SM elders. Indeed, social support has been proposed as a protective factor warranting future investigation.

An ecological animal model of subthreshold depression in adolescence: behavioral and resting state 18F-FDG PET imaging characterization

The different depressive disorders that exist can take root at adolescence. For instance, some functional and structural changes in several brain regions have been observed from adolescence in subjects that display either high vulnerability to depressive symptoms or subthreshold depression. For instance, adolescents with depressive disorder have been shown to exhibit hyperactivity in hippocampus, amygdala and prefrontal cortex as well as volume reductions in hippocampus and amygdala (prefrontal cortex showing more variable results). However, no animal model of adolescent subthreshold depression has been developed so far. Our objective was to design an animal model of adolescent subthreshold depression and to characterize the neural changes associated to this phenotype. For this purpose, we used adolescent Swiss mice that were evaluated on 4 tests assessing cognitive abilities (Morris water maze), anhedonia (sucrose preference), anxiety (open-field) and stress-coping strategies (forced swim test) at postnatal day (PND) 28–35. In order to identify neural alterations associated to behavioral profiles, we assessed brain resting state metabolic activity in vivo using 18F-FDG PET imaging at PND 37. We selected three profiles of mice distinguished in a composite Z-score computed from performances in the behavioral tests: High, Intermediate and Low Depressive Risk (HDR, IDR and LDR). Compared to both IDR and LDR, HDR mice were characterized by passive stress-coping behaviors, low cognition and high anhedonia and anxiety and were associated with significant changes of 18F-FDG uptakes in several cortical and subcortical areas including prelimbic cortex, infralimbic cortex, nucleus accumbens, amygdala, periaqueductal gray and superior colliculus, all displaying higher metabolic activity, while only the thalamus was associated with lower metabolic activity (compared to IDR). LDR displayed an opposing behavioral phenotype and were associated with significant changes of 18F-FDG uptakes in the dorsal striatum and thalamus that both exhibited markedly lower metabolic activity in LDR. In conclusion, our study revealed changes in metabolic activities that can represent neural signatures for behavioral profiles predicting subthreshold depression at adolescence in a mouse model.

The Dominance of Anticipatory Prefrontal Activity in Uncued Sensory-Motor Tasks.

Anticipatory event-related potentials (ERPs) precede upcoming events such as stimuli or actions. These ERPs are usually obtained in cued sensory–motor tasks employing a warning stimulus that precedes a probe stimulus as in the contingent negative variation (CNV) paradigms. The CNV wave has been widely studied, from clinical to brain–computer interface (BCI) applications, and has been shown to emerge in medial frontoparietal areas, localized in the cingulate and supplementary motor areas. Several dated studies also suggest the existence of a prefrontal CNV, although this component was not confirmed by later studies due to the contamination of ocular artifacts. Another lesser-known anticipatory ERP is the prefrontal negativity (pN) that precedes the uncued probe stimuli in discriminative response tasks and has been localized in the inferior frontal gyrus. This study aimed to characterize the pN by comparing it with the CNV in cued and uncued tasks and test if the pN could be associated with event preparation, temporal preparation, or both. To achieve these aims, high-density electroencephalographic recording and advanced ERP analysis controlling for ocular activity were obtained in 25 volunteers who performed 4 different visuomotor tasks. Our results showed that the pN amplitude was largest in the condition requiring both time and event preparation, medium in the condition requiring event preparation only, and smallest in the condition requiring temporal preparation only. We concluded that the prefrontal CNV could be associated with the pN, and this activity emerges in complex tasks requiring the anticipation of both the category and timing of the upcoming stimulus. The proposed method can be useful in BCI studies investigating the endogenous neural signatures triggered by different sensorimotor paradigms.

Integrated cognitive and physical fitness training enhances attention abilities in older adults

Preserving attention abilities is of great concern to older adults who are motivated to maintain their quality of life. Both cognitive and physical fitness interventions have been utilized in intervention studies to assess maintenance and enhancement of attention abilities in seniors, and a coupling of these approaches is a compelling strategy to buttress both cognitive and physical health in a time- and resource-effective manner. With this perspective, we created a closed-loop, motion-capture video game (Body-Brain Trainer: BBT) that adapts a player’s cognitive and physical demands in an integrated approach, thus creating a personalized and cohesive experience across both domains. Older adults who engaged in two months of BBT improved on both physical fitness (measures of blood pressure and balance) and attention (behavioral and neural metrics of attention on a continuous performance task) outcome measures beyond that of an expectancy matched, active, placebo control group, with maintenance of improved attention performance evidenced 1 year later. Following training, the BBT group’s improvement on the attention outcome measure exceeded performance levels attained by an untrained group of 20-year olds, and showed age-equilibration of a neural signature of attention shown to decline with age: midline frontal theta power. These findings highlight the potential benefits of an integrated, cognitive-physical, closed-loop training platform as a powerful tool for both cognitive and physical enhancement in older adults.

Distinct neural representations for prosocial and self-benefiting effort

Prosocial behaviors-actions that benefit others-are central to individual and societal well-being. Although the mechanisms underlying the financial and moral costs of prosocial behaviors are increasingly understood, this work has often ignored a key influence on behavior: effort. Many prosocial acts are effortful, and people are averse to the costs of exerting them. However, how the brain encodes effort costs when actions benefit others is unknown. During fMRI, participants completed a decision-making task where they chose in each trial whether to "work" and exert force (30%-70% of maximum grip strength) or "rest" (no effort) for rewards (2-10 credits). Crucially, on separate trials, they made these decisions either to benefit another person or themselves. We used a combination of multivariate representational similarity analysis and model-based univariate analysis to reveal how the costs of prosocial and self-benefiting efforts are processed. Strikingly, we identified a unique neural signature of effort in the anterior cingulate gyrus (ACCg) for prosocial acts, both when choosing to help others and when exerting force to benefit them. This pattern was absent for self-benefiting behaviors. Moreover, stronger, specific representations of prosocial effort in the ACCg were linked to higher levels of empathy and higher subsequent exerted force to benefit others. In contrast, the ventral tegmental area and ventral insula represented value preferentially when choosing for oneself and not for prosocial acts. These findings advance our understanding of the neural mechanisms of prosocial behavior, highlighting the critical role that effort has in the brain circuits that guide helping others.

A shared numerical magnitude representation evidenced by the distance effect in frequency-tagging EEG

Humans can effortlessly abstract numerical information from various codes and contexts. However, whether the access to the underlying magnitude information relies on common or distinct brain representations remains highly debated. Here, we recorded electrophysiological responses to periodic variation of numerosity (every five items) occurring in rapid streams of numbers presented at 6 Hz in randomly varying codes—Arabic digits, number words, canonical dot patterns and finger configurations. Results demonstrated that numerical information was abstracted and generalized over the different representation codes by revealing clear discrimination responses (at 1.2 Hz) of the deviant numerosity from the base numerosity, recorded over parieto-occipital electrodes. Crucially, and supporting the claim that discrimination responses reflected magnitude processing, the presentation of a deviant numerosity distant from the base (e.g., base “2” and deviant “8”) elicited larger right-hemispheric responses than the presentation of a close deviant numerosity (e.g., base “2” and deviant “3”). This finding nicely represents the neural signature of the distance effect, an interpretation further reinforced by the clear correlation with individuals’ behavioral performance in an independent numerical comparison task. Our results therefore provide for the first time unambiguously a reliable and specific neural marker of a magnitude representation that is shared among several numerical codes.

Neural signatures of evidence accumulation in temporal decisions

Cognitive models of interval timing can be formulated as an accumulation-to-bound process.1-5 However, the physiological manifestation of such processes has not yet been identified. We used electroencephalography (EEG) to measure the neural responses of participants while they performed a temporal bisection task in which they were requested to categorize the duration of visual stimuli as short or long.6 We found that the stimulus-offset and response-locked activity depends on both stimulus duration and the participants' decision. To relate this activity to the underlying cognitive processes, we used a drift-diffusion model.7 The model includes a noisy accumulator starting with the stimulus onset and a decision threshold. According to the model, a stimulus duration will be categorized as "long" if the accumulator reaches the threshold during stimulus presentation. Otherwise, it will be categorized as "short." We found that at the offset of stimulus presentation, an EEG response marks the distance of the accumulator from the threshold. Therefore, this model offers an accurate description of our behavioral data as well as the EEG response using the same two model parameters. We then replicated this finding in an identical experiment conducted in the tactile domain. We also extended this finding to two different temporal ranges (sub- and supra-second). Taken together, the work provides a new way to study the cognitive processes underlying temporal decisions, using a combination of behavior, EEG, and modeling.

Intrinsic brain activity patterns across large-scale networks predict reciprocity propensity.

Reciprocity is prevalent across human societies, but individuals are heterogeneous regarding their reciprocity propensity. Although a large body of task-based brain imaging measures has shed light on the neural underpinnings of reciprocity at group level, the neural basis underlying the individual differences in reciprocity propensity remains largely unclear. Here, we combined brain imaging and machine learning techniques to individually predict reciprocity propensity from resting-state brain activity measured by fractional amplitude of low-frequency fluctuation. The brain regions contributing to the prediction were then analyzed for functional connectivity and decoding analyses, allowing for a data-driven quantitative inference on psychophysiological functions. Our results indicated that patterns of resting-state brain activity across multiple brain systems were capable of predicting individual reciprocity propensity, with the contributing regions distributed across the salience (e.g., ventrolateral prefrontal cortex), fronto-parietal (e.g., dorsolateral prefrontal cortex), default mode (e.g., ventromedial prefrontal cortex), and sensorimotor (e.g., supplementary motor area) networks. Those contributing brain networks are implicated in emotion and cognitive control, mentalizing, and motor-based processes, respectively. Collectively, these findings provide novel evidence on the neural signatures underlying the individual differences in reciprocity, and lend support the assertion that reciprocity emerges from interactions among regions embodied in multiple large-scale brain networks.

Network modeling of dynamic brain interactions predicts emergence of neural information that supports human cognitive behavior.

How cognitive task behavior is generated by brain network interactions is a central question in neuroscience. Answering this question calls for the development of novel analysis tools that can firstly capture neural signatures of task information with high spatial and temporal precision (the “where and when”) and then allow for empirical testing of alternative network models of brain function that link information to behavior (the “how”). We outline a novel network modeling approach suited to this purpose that is applied to noninvasive functional neuroimaging data in humans. We first dynamically decoded the spatiotemporal signatures of task information in the human brain by combining MRI-individualized source electroencephalography (EEG) with multivariate pattern analysis (MVPA). A newly developed network modeling approach—dynamic activity flow modeling—then simulated the flow of task-evoked activity over more causally interpretable (relative to standard functional connectivity [FC] approaches) resting-state functional connections (dynamic, lagged, direct, and directional). We demonstrate the utility of this modeling approach by applying it to elucidate network processes underlying sensory–motor information flow in the brain, revealing accurate predictions of empirical response information dynamics underlying behavior. Extending the model toward simulating network lesions suggested a role for the cognitive control networks (CCNs) as primary drivers of response information flow, transitioning from early dorsal attention network-dominated sensory-to-response transformation to later collaborative CCN engagement during response selection. These results demonstrate the utility of the dynamic activity flow modeling approach in identifying the generative network processes underlying neurocognitive phenomena.

Delay-related activity in marmoset prefrontal cortex.

Persistent delay-period activity in prefrontal cortex (PFC) has long been regarded as a neural signature of working memory (WM). Electrophysiological investigations in macaque PFC have provided much insight into WM mechanisms; however, a barrier to understanding is the fact that a portion of PFC lies buried within the principal sulcus in this species and is inaccessible for laminar electrophysiology or optical imaging. The relatively lissencephalic cortex of the New World common marmoset (Callithrix jacchus) circumvents such limitations. It remains unknown, however, whether marmoset PFC neurons exhibit persistent activity. Here, we addressed this gap by conducting wireless electrophysiological recordings in PFC of marmosets performing a delayed-match-to-location task on a home cage-based touchscreen system. As in macaques, marmoset PFC neurons exhibited sample-, delay-, and response-related activity that was directionally tuned and linked to correct task performance. Models constructed from population activity consistently and accurately predicted stimulus location throughout the delay period, supporting a framework of delay activity in which mnemonic representations are relatively stable in time. Taken together, our findings support the existence of common neural mechanisms underlying WM performance in PFC of macaques and marmosets and thus validate the marmoset as a suitable model animal for investigating the microcircuitry underlying WM.

Causal Inference of Body Ownership in the Posterior Parietal Cortex.

How do we come to sense that a hand in view belongs to our own body or not? Previous studies have suggested that the integration of vision and somatosensation in the frontoparietal areas plays a critical role in the sense of body ownership (i.e., the multisensory perception of limbs and body parts as our own). However, little is known about how these areas implement the multisensory integration process at the computational level and whether activity predicts illusion elicitation in individual participants on a trial-by-trial basis. To address these questions, we used functional magnetic resonance imaging and a rubber hand illusion-detection task and fitted the registered neural responses to a Bayesian causal inference model of body ownership. Thirty healthy human participants (male and female) performed 12 s trials with varying degrees of asynchronously delivered visual and tactile stimuli of a rubber hand (in view) and a (hidden) real hand. After the 12 s period, participants had to judge whether the rubber hand felt like their own. As hypothesized, activity in the premotor and posterior parietal cortices was related to illusion elicitation at the level of individual participants and trials. Importantly, activity in the posterior parietal cortex fit the predicted probability of illusion emergence of the Bayesian causal inference model based on each participant's behavioral response profile. Our findings suggest an important role for the posterior parietal cortex in implementing Bayesian causal inference of body ownership and reveal how trial-by-trial variations in neural signatures of multisensory integration relate to the elicitation of the rubber hand illusion.SIGNIFICANCE STATEMENT How does the brain create a coherent perceptual experience of one's own body based on information from the different senses? We examined how the likelihood of eliciting a classical bodily illusion that depends on vision and touch—the rubber hand illusion—is related to neural activity measured by functional magnetic resonance imaging. We found that trial-by-trial variations in the neural signal in the posterior parietal cortex, a well known center for sensory integration, fitted a statistical function that describes how likely it is that the brain infers that a rubber hand is one's own given the available visual and tactile evidence. Thus, probabilistic analysis of sensory information in the parietal lobe underlies our unitary sense of bodily self.

A hierarchy of linguistic predictions during natural language comprehension

Understanding spoken language requires transforming ambiguous acoustic streams into a hierarchy of representations, from phonemes to meaning. It has been suggested that the brain uses prediction to guide the interpretation of incoming input. However, the role of prediction in language processing remains disputed, with disagreement about both the ubiquity and representational nature of predictions. Here, we address both issues by analyzing brain recordings of participants listening to audiobooks, and using a deep neural network (GPT-2) to precisely quantify contextual predictions. First, we establish that brain responses to words are modulated by ubiquitous predictions. Next, we disentangle model-based predictions into distinct dimensions, revealing dissociable neural signatures of predictions about syntactic category (parts of speech), phonemes, and semantics. Finally, we show that high-level (word) predictions inform low-level (phoneme) predictions, supporting hierarchical predictive processing. Together, these results underscore the ubiquity of prediction in language processing, showing that the brain spontaneously predicts upcoming language at multiple levels of abstraction.

MITF deficiency and oncogenic GNAQ each promote proliferation programs in zebrafish melanocyte lineage cells.

Uveal melanoma (UM) is the most common primary malignancy of the adult eye but lacks any FDA‐approved therapy for the deadly metastatic disease. Thus, there is a great need to dissect the driving mechanisms for UM and develop strategies to evaluate potential therapeutics. Using an autochthonous zebrafish model, we previously identified MITF, the master melanocyte transcription factor, as a tumor suppressor in GNAQQ209L‐driven UM. Here, we show that zebrafish mitfa‐deficient GNAQQ209L‐driven tumors significantly up‐regulate neural crest markers, and that higher expression of a melanoma‐associated neural crest signature correlates with poor UM patient survival. We further determined how the mitfa‐null state, as well as expression of GNAQQ209L, YAPS127A;S381A, or BRAFV600E oncogenes, impacts melanocyte lineage cells before they acquire the transformed state. Specifically, examination 5 days post‐fertilization showed that mitfa‐deficiency is sufficient to up‐regulate pigment progenitor and neural crest markers, while GNAQQ209L expression promotes a proliferative phenotype that is further enhanced by YAPS127A;S381A co‐expression. Finally, we show that this oncogene‐induced proliferative phenotype can be used to screen chemical inhibitors for their efficacy against the UM pathway. Overall, this study establishes that a neural crest signature correlates with poor UM survival, and describes an in vivo assay for preclinical trials of potential UM therapeutics.

Neural Signatures of Pain Modulation in Short-Term and Long-Term Mindfulness Training: A Randomized Active-Control Trial.

Mindfulness-based interventions are widely used to target pain, yet their neural mechanisms of action are insufficiently understood. The authors studied neural and subjective pain response in a randomized active-control trial of mindfulness-based stress reduction (MBSR) alongside long-term meditation practitioners. Healthy participants (N=115) underwent functional neuroimaging during a thermal acute pain task before and after random assignment to MBSR (N=28), an active control condition (health enhancement program [HEP]) (N=32), or a waiting list control condition (N=31). Long-term meditators (N=30) completed the same neuroimaging paradigm. Pain response was measured via self-reported intensity and unpleasantness, and neurally via two multivoxel machine-learning-derived signatures: the neurologic pain signature (NPS), emphasizing nociceptive pain processing, and the stimulus intensity independent pain signature-1 (SIIPS1), emphasizing stimulus-independent neuromodulatory processes. The MBSR group showed a significant decrease in NPS response relative to the HEP group (Cohen's d=-0.43) and from pre- to postintervention assessment (d=-0.47). The MBSR group showed small, marginal decreases in NPS relative to the waiting list group (d=-0.36), and in SIIPS1 relative to both groups (HEP group, d=-0.37; waiting list group, d=-0.37). In subjective unpleasantness, the MBSR and HEP groups also showed modest significant reductions compared with the waiting list group (d=-0.45 and d=-0.55). Long-term meditators reported significantly lower pain than nonmeditators but did not differ in neural response. Within the long-term meditator group, cumulative practice during intensive retreat was significantly associated with reduced SIIPS1 (r=-0.65), whereas daily practice was not. Mindfulness training showed associations with pain reduction that implicate differing neural pathways depending on extent and context of practice. Use of neural pain signatures in randomized trials offers promise for guiding the application of mindfulness interventions to pain treatment.

The neurobiology of misophonia and implications for novel, neuroscience-driven interventions.

Decreased tolerance in response to specific every-day sounds (misophonia) is a serious, debilitating disorder that is gaining rapid recognition within the mental health community. Emerging research findings suggest that misophonia may have a unique neural signature. Specifically, when examining responses to misophonic trigger sounds, differences emerge at a physiological and neural level from potentially overlapping psychopathologies. While these findings are preliminary and in need of replication, they support the hypothesis that misophonia is a unique disorder. In this theoretical paper, we begin by reviewing the candidate networks that may be at play in this complex disorder (e.g., regulatory, sensory, and auditory). We then summarize current neuroimaging findings in misophonia and present areas of overlap and divergence from other mental health disorders that are hypothesized to co-occur with misophonia (e.g., obsessive compulsive disorder). Future studies needed to further our understanding of the neuroscience of misophonia will also be discussed. Next, we introduce the potential of neurostimulation as a tool to treat neural dysfunction in misophonia. We describe how neurostimulation research has led to novel interventions in psychiatric disorders, targeting regions that may also be relevant to misophonia. The paper is concluded by presenting several options for how neurostimulation interventions for misophonia could be crafted.

Long-term memory retrieval bypasses working memory

For decades, it has been assumed that when humans retrieve information from long-term memory (LTM), information need first to be brought back into working memory (WM). However, as WM capacity is limited, it is unclear what happens if information from LTM needs to be retrieved while WM is fully engaged? To address this question, observers had to retrieve colors from LTM while WM storage capacity was fully engaged. The behavioral results showed that retrieving information from LTM is possible even when WM capacity is fully occupied. Additional evidence from electroencephalogram (EEG) confirmed that WM was fully engaged as the suppression of alpha oscillation reached its maximum when memorizing the maximum amount of information into WM; yet the suppression in alpha oscillation was even further amplified when items were retrieved simultaneously from LTM, providing a neural signature of additional LTM retrieval capacity above and beyond the maximum WM capacity. Together, our findings indicate that information retrieved from LTM does not always have to be brought back into WM, but instead might be accessed through a different mechanism when WM is fully engaged.

Baseline hippocampal beta band power is lower in the presence of movement uncertainty

Objective. This study aimed to characterize hippocampal neural signatures of uncertainty by measuring beta band power in the period prior to movement cue. Approach. Participants with epilepsy were implanted with hippocampal depth electrodes for stereo electroencephalographic (SEEG) monitoring. Hippocampal beta (13–30 Hz) power changes have been observed during motor tasks such as the direct reach (DR) and Go/No-Go (GNG) tasks. The primary difference between the tasks is the presence of uncertainty about whether movement should be executed. Previous research on cortical responses to uncertainty has found that baseline beta power changes with uncertainty. SEEG data were sampled throughout phases of the DR and GNG tasks. Beta-band power during the fixation phase was compared between the DR and GNG task using a Wilcoxon rank sum test. This unpaired test was also used to analyze response times from cue to task completion between tasks. Main results. Eight patients who performed both reaching tasks were analyzed in this study. Movement response times in the GNG task were on average 210 milliseconds slower than in the DR task. All patients exhibited a significantly increased response latency in the GNG task compared to the DR task (Wilcoxon rank-sum p-value < 0.001). Six out of eight patients demonstrated statistically significant differences in beta power in single hippocampal contacts between the fixation phases of the GNG and DR tasks. At the group level, baseline beta power was significantly lower in the GNG task than in the DR task (Wilcoxon rank-sum p-value < 0.001). Significance. This novel study found that, in the presence of task uncertainty, baseline beta power in the hippocampus is lower than in its absence. This finding implicates movement uncertainty as an important factor in baseline hippocampal beta power during movement preparation.

Mental Activity as the Bridge between Neural Biomarkers and Symptoms of Psychiatric Illness.

The Research Domain Criteria (RDoC) initiative challenges researchers to build neurobehavioral models of psychiatric illness with the hope that such models identify better targets that will yield more effective treatment. However, a guide for building such models was not provided and symptom heterogeneity within Diagnostic Statistical Manual categories has hampered progress in identifying endophenotypes that underlie mental illness. We propose that the best chance to discover viable biomarkers and treatment targets for psychiatric illness is to investigate a triangle of relationships: severity of a specific psychiatric symptom that correlates to mental activity that correlates to a neural activity signature. We propose that this is the minimal model complexity required to advance the field of psychiatry. With an understanding of how neural activity relates to the experience of the patient, a genuine understanding for how treatment imparts its therapeutic effect is possible. After the discovery of this three-fold relationship, causal testing is required in which the neural activity pattern is directly enhanced or suppressed to provide causal, instead of just correlational, evidence for the biomarker. We suggest using non-invasive brain stimulation (NIBS) as these techniques provide tools to precisely manipulate spatial and temporal activity patterns. We detail how this approach enabled the discovery of two orthogonal electroencephalography (EEG) activity patterns associated with anhedonia and anxiosomatic symptoms in depression that can serve as future treatment targets. Altogether, we propose a systematic approach for building neurobehavioral models for dimensional psychiatry.

A neural signature of exposure to masked faces after 18 months of COVID-19

In the last two years, face-to-face interactions have drastically changed worldwide, because of the COVID-19 pandemic: the persistent use of masks has had the advantage of reducing viral transmission, but it has also had the cost of impacting on the perception and recognition of social information from faces, especially emotions. To assess the cerebral counterpart to this condition, we carried out an EEG experiment, extracting Event-Related Potentials (ERPs) evoked by emotional faces with and without surgical masks. Besides the expected impairment in emotion recognition in both accuracy and response times, also the classical face-related ERPs (N170 and P2) are altered by the presence of surgical masks. Importantly, the effect is stronger in individuals with a lower daily exposure to masks, suggesting that the brain must adapt to an extra constraint in decoding social input, due to masks hiding crucial facial information.

Distinct neural correlates of poor decoding and poor comprehension in children with reading disability.

Reading disability (RD) can manifest itself as a word decoding problem or a reading comprehension problem. In the current study, we identified 3 subtypes of RD: poor decoders (PD), poor comprehenders (PC), and poor-in-both (PB). We found that PD had greater deficits in meta-linguistic skills such as phonological awareness, orthographic skills, and morphological skills than PC, whereas PC had greater deficits in listening comprehension than PD. In the brain, we also found different patterns of deficits during an auditory rhyming judgment task using functional magnetic resonance imaging. PD showed less activation than PC and age controls in the left dorsal inferior frontal gyrus (IFG) and pre-supplementary motor area (SMA), brain activation of which was correlated with phonological awareness and working memory. In contrast, PC showed less activation in the left fusiform gyrus than PD and age controls, which was correlated with reading comprehension fluency and morphological skill. Last, PB showed both PD's and PC's deficits, as well as additional deficits in the bilateral lingual gyri. Our findings contribute to revealing different neural signatures of poor decoding and poor comprehension, which are distinct disorders but co-occur very often. These findings implicate possibility and necessity of precise diagnosis and individualized intervention.