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Objective: Mind-wandering is a pervasive human brain state and, when in excess, may promote negative affect and neuropsychiatric conditions. Mindfulness meditation may promote alternate brain states, improving affect and reducing stress. An understanding of the neural basis between these brain states could thus advance treatment of neuropsychiatric conditions, including those associated with epilepsy., Methods: To explore the neural basis of mindfulness meditation versus mind-wandering, we enrolled eight patients in a trial of structured mindfulness meditation and open mind-wandering who underwent stereo electroencephalography (sEEG) within the mesial temporal lobe for seizure localization. Electrophysiology was compared between mind-wandering and mindfulness separately for epileptic and non-epileptic MTL. Using fitting-one-over-f modeling, periodic components of electrophysiology were compared in canonical frequency bands of theta (4-8 Hz), alpha (8-13 Hz), beta (13-30 Hz), and gamma (30-55 Hz). Aperiodic components of the power spectra were assessed by the model offset, knee, and exponent., Results: We found a significant reduction in gamma power (30-55 Hz) within the mesial temporal lobe (MTL) during mindfulness meditation compared with mind-wandering in non-epileptic (p = 1.20E-4) but not in epileptic MTL (p = 0.352).There was also a significant difference between epileptic versus non-epileptic MTL in gamma power between conditions (p = 0.011). There were no significant changes in power across any frequency band within epileptic mesial temporal MTL between brain states. Conversely, there were significant differences between mind-wandering and mindfulness within epileptic MTL in aperiodic components (offset, knee, and exponent, all p < 0.05), while no differences in aperiodic components were seen in non-epileptic MTL (all p > 0.70)., Significance: Intracranial electrophysiologic modulations between brain state (mind-wandering versus mindfulness) may differ between epileptic and non-epileptic MTL. Modulations in gamma activity in non-epileptic MTL may represent functional changes in brain state, while aperiodic changes in epileptic MTL may modulate propensity for seizures., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dr. Fedor Panov, MD is a paid speaker for NeuroPace. The remaining authors have no conflicts of interest. We confirm that we have read the Journal’s position on issues involved in ethical publication and affirm that this report is consistent with those guidelines., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The neurophysiological mechanisms supporting brain maturation are fundamental to attention and memory capacity across the lifespan. Human brain regions develop at different rates, with many regions developing into the third and fourth decades of life. Here, in this preregistered study (https://osf.io/gsru7), we analyzed intracranial EEG (iEEG) recordings from widespread brain regions in a large developmental cohort. Using task-based (i.e., attention to-be-remembered visual stimuli) and task-free (resting-state) data from 101 children and adults (5.93 - 54.00 years, 63 males; n electrodes = 5691), we mapped aperiodic (1/ƒ-like) activity, a proxy of excitation:inhibition (E:I) balance with steeper slopes indexing inhibition and flatter slopes indexing excitation. We reveal that aperiodic slopes flatten with age into young adulthood in both association and sensorimotor cortices, challenging models of early sensorimotor development based on brain structure. In prefrontal cortex (PFC), attentional state modulated age effects, revealing steeper task-based than task-free slopes in adults and the opposite in children, consistent with the development of cognitive control. Age-related differences in task-based slopes also explained age-related gains in memory performance, linking the development of PFC cognitive control to the development of memory. Last, with additional structural imaging measures, we reveal that age-related differences in gray matter volume are differentially associated with aperiodic slopes in association and sensorimotor cortices. Our findings establish developmental trajectories of aperiodic activity in localized brain regions and illuminate the development of PFC inhibitory control during adolescence in the development of attention and memory.

How our decisions impact our memories is not well understood. Reward prediction errors (RPEs), the difference between expected and obtained reward, help us learn to make optimal decisions-providing a signal that may influence subsequent memory. To measure this influence and how it might go awry in mood disorders, we recruited a large cohort of human participants to perform a decision-making task in which perceptually memorable stimuli were associated with probabilistic rewards, followed by a recognition test for those stimuli. Computational modeling revealed that positive RPEs enhanced both the accuracy of memory and the temporal efficiency of memory search, beyond the contribution of perceptual information. Critically, positive affect upregulated the beneficial effect of RPEs on memory. These findings demonstrate how affect selectively regulates the impact of RPEs on memory, providing a computational mechanism for biased memory in mood disorders., (© 2024. The Author(s).)

The prefrontal cortex (PFC) is a region of the brain that in humans is involved in the production of higher-order functions such as cognition, emotion, perception, and behavior. Neurotransmission in the PFC produces higher-order functions by integrating information from other areas of the brain. At the foundation of neurotransmission, and by extension at the foundation of higher-order brain functions, are an untold number of coordinated molecular processes involving the DNA sequence variants in the genome, RNA transcripts in the transcriptome, and proteins in the proteome. These "multiomic" foundations are poorly understood in humans, perhaps in part because most modern studies that characterize the molecular state of the human PFC use tissue obtained when neurotransmission and higher-order brain functions have ceased (i.e., the postmortem state). Here, analyses are presented on data generated for the Living Brain Project (LBP) to investigate whether PFC tissue from individuals with intact higher-order brain function has characteristic multiomic foundations. Two complementary strategies were employed towards this end. The first strategy was to identify in PFC samples obtained from living study participants a signature of RNA transcript expression associated with neurotransmission measured intracranially at the time of PFC sampling, in some cases while participants performed a task engaging higher-order brain functions. The second strategy was to perform multiomic comparisons between PFC samples obtained from individuals with intact higher-order brain function at the time of sampling (i.e., living study participants) and PFC samples obtained in the postmortem state. RNA transcript expression within multiple PFC cell types was associated with fluctuations of dopaminergic, serotonergic, and/or noradrenergic neurotransmission in the substantia nigra measured while participants played a computer game that engaged higher-order brain functions. A subset of these associations - termed the "transcriptional program associated with neurotransmission" (TPAWN) - were reproduced in analyses of brain RNA transcript expression and intracranial neurotransmission data obtained from a second LBP cohort and from a cohort in an independent study. RNA transcripts involved in TPAWN were found to be (1) enriched for RNA transcripts associated with measures of neurotransmission in rodent and cell models, (2) enriched for RNA transcripts encoded by evolutionarily constrained genes, (3) depleted of RNA transcripts regulated by common DNA sequence variants, and (4) enriched for RNA transcripts implicated in higher-order brain functions by human population genetic studies. In PFC excitatory neurons of living study participants, higher expression of the genes in TPAWN tracked with higher expression of RNA transcripts that in rodent PFC samples are markers of a class of excitatory neurons that connect the PFC to deep brain structures. TPAWN was further reproduced by RNA transcript expression patterns differentiating living PFC samples from postmortem PFC samples, and significant differences between living and postmortem PFC samples were additionally observed with respect to (1) the expression of most primary RNA transcripts, mature RNA transcripts, and proteins, (2) the splicing of most primary RNA transcripts into mature RNA transcripts, (3) the patterns of co-expression between RNA transcripts and proteins, and (4) the effects of some DNA sequence variants on RNA transcript and protein expression. Taken together, this report highlights that studies of brain tissue obtained in a safe and ethical manner from large cohorts of living individuals can help advance understanding of the multiomic foundations of brain function.

Dopamine (DA) signals originating from substantia nigra (SN) neurons are centrally involved in the regulation of motor and reward processing. DA signals behaviorally relevant events where reward outcomes differ from expectations (reward prediction errors, RPEs). RPEs play a crucial role in learning optimal courses of action and in determining response vigor when an agent expects rewards. Nevertheless, how reward expectations, crucial for RPE calculations, are conveyed to and represented in the dopaminergic system is not fully understood, especially in the human brain where the activity of DA neurons is difficult to study. One possibility, suggested by evidence from animal models, is that DA neurons explicitly encode reward expectations. Alternatively, they may receive RPE information directly from upstream brain regions. To address whether SN neuron activity directly reflects reward expectation information, we directly examined the encoding of reward expectation signals in human putative DA neurons by performing single-unit recordings from the SN of patients undergoing neurosurgery. Patients played a two-armed bandit decision-making task in which they attempted to maximize reward. We show that neuronal firing rates (FR) of putative DA neurons during the reward expectation period explicitly encode reward expectations. First, activity in these neurons was modulated by previous trial outcomes, such that FR were greater after positive outcomes than after neutral or negative outcome trials. Second, this increase in FR was associated with shorter reaction times, consistent with an invigorating effect of DA neuron activity during expectation. These results suggest that human DA neurons explicitly encode reward expectations, providing a neurophysiological substrate for a signal critical for reward learning.

Dopamine and serotonin are hypothesized to guide social behaviours. In humans, however, we have not yet been able to study neuromodulator dynamics as social interaction unfolds. Here, we obtained subsecond estimates of dopamine and serotonin from human substantia nigra pars reticulata during the ultimatum game. Participants, who were patients with Parkinson's disease undergoing awake brain surgery, had to accept or reject monetary offers of varying fairness from human and computer players. They rejected more offers in the human than the computer condition, an effect of social context associated with higher overall levels of dopamine but not serotonin. Regardless of the social context, relative changes in dopamine tracked trial-by-trial changes in offer value-akin to reward prediction errors-whereas serotonin tracked the current offer value. These results show that dopamine and serotonin fluctuations in one of the basal ganglia's main output structures reflect distinct social context and value signals., (© 2024. The Author(s).)

Depression is prevalent in epilepsy patients and their intracranial brain activity recordings can be used to determine the types of brain activity that are associated with comorbid depression. We performed case-control comparison of spectral power and phase amplitude coupling (PAC) in 34 invasively monitored drug resistant epilepsy patients' brain recordings. The values of spectral power and PAC for one-minute segments out of every hour in a patient's study were correlated with pre-operative assessment of depressive symptoms by Beck Depression Inventory-II (BDI). We identified an elevated PAC signal (theta-alpha-beta phase (5-25 Hz)/gamma frequency (80-100 Hz) band) that is present in high BDI scores but not low BDI scores adult epilepsy patients in brain regions implicated in primary depression, including anterior cingulate cortex, amygdala and orbitofrontal cortex. Our results showed the application of PAC as a network-specific, electrophysiologic biomarker candidate for comorbid depression and its potential as treatment target for neuromodulation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Objective: Non-literal expressions such as sarcasm, metaphor and simile refer to words and sentences that convey meanings or intentions that are different and more abstract than literal expressions. Neuroimaging studies have shown activations in a variety of frontal, parietal and temporal brain regions implicated in non-literal language processing. However, neurophysiological correlates of these brain areas underlying non-literal processing remain underexplored., Methods: To address this, we investigated patterns of intracranial EEG activity during non-literal processing by leveraging a unique patient population. Seven neurosurgical patients with invasive electrophysiological monitoring of superficial brain activity were recruited. Intracranial neural responses were recorded over the temporal-parietal junction (TPJ) and its surrounding areas while patients performed a language task. Participants listened to vignettes that ended with non-literal or literal statements and were then asked related questions to which they responded verbally., Results: We found differential neurophysiological activity during the processing of non-literal statements as compared to literal statements, especially in low-Gamma (30-70 Hz) and delta (1-4 Hz) bands. In addition, we found that neural responses related to non-literal processing in the high-gamma band (>70 Hz) were significantly more prominent at TPJ electrodes as compared to non-TPJ (i.e., control) electrodes in most subjects. Moreover, in half of patients, high-gamma activity related to non-literal processing was accompanied by delta-band modulation., Conclusion: These results suggest that both low- and high-frequency electrophysiological activities in the temporal-parietal junction play a crucial role during non-literal language processing in the human brain. The current investigation, utilizing better spatial and temporal resolution of human intracranial electrocorticography, provides a unique opportunity to gain insights into the localized brain dynamics of the TPJ during the processing of non-literal language expressions., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Soni, Overton, Kam, Pexman, Prabhu, Garza, Saez and Girgis.)

Social decision making requires the integration of reward valuation and social cognition systems, both dependent on the orbitofrontal cortex (OFC). How these two OFC functions interact is largely unknown. We recorded intracranial activity from the OFC of ten patients making choices in a social context where reward inequity with a social counterpart varied and could be either advantageous or disadvantageous. We find that OFC high-frequency activity (HFA; 70-150 Hz) encodes self-reward, consistent with previous reports. We also observe encoding of the social counterpart's reward, as well as the type of inequity being experienced. Additionally, we find evidence of inequity-dependent reward encoding: depending on the type of inequity, electrodes rapidly and reversibly switch between different reward-encoding profiles. These results provide direct evidence for encoding of self- and other rewards in the human OFC and highlight the dynamic nature of encoding in the OFC as a function of social context., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Flexible behavior requires gating mechanisms that encode only task-relevant information in working memory. Extant literature supports a theoretical division of labor whereby lateral frontoparietal interactions underlie information maintenance and the striatum enacts the gate. Here, we reveal neocortical gating mechanisms in intracranial EEG patients by identifying rapid, within-trial changes in regional and inter-regional activities that predict subsequent behavioral outputs. Results first demonstrate information accumulation mechanisms that extend prior fMRI (i.e., regional high-frequency activity) and EEG evidence (inter-regional theta synchrony) of distributed neocortical networks in working memory. Second, results demonstrate that rapid changes in theta synchrony, reflected in changing patterns of default mode network connectivity, support filtering. Graph theoretical analyses further linked filtering in task-relevant information and filtering out irrelevant information to dorsal and ventral attention networks, respectively. Results establish a rapid neocortical theta network mechanism for flexible information encoding, a role previously attributed to the striatum., (© 2023. The Author(s).)

Computational psychiatry, a relatively new yet prolific field that aims to understand psychiatric disorders with formal theories about the brain, has seen tremendous growth in the past decade. Despite initial excitement, actual progress made by computational psychiatry seems stagnant. Meanwhile, understanding of the human brain has benefited tremendously from recent progress in intracranial neuroscience. Specifically, invasive techniques such as stereotactic electroencephalography, electrocorticography, and deep brain stimulation have provided a unique opportunity to precisely measure and causally modulate neurophysiological activity in the living human brain. In this review, we summarize progress and drawbacks in both computational psychiatry and invasive electrophysiology and propose that their combination presents a highly promising new direction-invasive computational psychiatry. The value of this approach is at least twofold. First, it advances our mechanistic understanding of the neural computations of mental states by providing a spatiotemporally precise depiction of neural activity that is traditionally unattainable using noninvasive techniques with human subjects. Second, it offers a direct and immediate way to modulate brain states through stimulation of algorithmically defined neural regions and circuits (i.e., algorithmic targeting), thus providing both causal and therapeutic insights. We then present depression as a use case where the combination of computational and invasive approaches has already shown initial success. We conclude by outlining future directions as a road map for this exciting new field as well as presenting cautions about issues such as ethical concerns and generalizability of findings., (Copyright © 2022 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Deep brain stimulation (DBS) is a well-established treatment for Parkinson's disease (PD). While the success of DBS is dependent on careful patient selection and accurate lead placement, programming parameters play a pivotal role in tailoring therapy on the individual level. Various algorithms have been developed to streamline the initial programming process, but the relationship between pre-operative patient characteristics and post-operative device settings is unclear. In this study, we investigated how PD severity correlates with DBS settings., Methods: We conducted a retrospective review of PD patients who underwent DBS of the subthalamic nucleus at one US tertiary care center between 2014 and 2018. Pre-operative patient characteristics and post-operative programming data at various intervals were collected. Disease severity was measured using the Unified Parkinson's Disease Rating Scale score (UPDRS) as well as levodopa equivalent dose (LED). Correlation analyses were conducted looking for associations between pre-operative disease severity and post-operative programming parameters., Results: Fifty-six patients were analyzed. There was no correlation between disease severity and any of the corresponding programming parameters. Pre-operative UPDRS scores on medication were similar to post-operative scores with DBS. Settings of amplitude, frequency, and pulse width increased significantly from 1 to 6 months post-operatively. Stimulation volume, inferred by the distance between contacts used, also increased significantly over time., Conclusions: Interestingly, we found that patients with more advanced disease responded to electrical stimulation similarly to patients with less advanced disease. These data provide foundational knowledge of DBS programming parameters used in a single cohort of PD patients over time., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

Despite increased awareness of the lack of gender equity in academia and a growing number of initiatives to address issues of diversity, change is slow, and inequalities remain. A major source of inequity is gender bias, which has a substantial negative impact on the careers, work-life balance, and mental health of underrepresented groups in science. Here, we argue that gender bias is not a single problem but manifests as a collection of distinct issues that impact researchers' lives. We disentangle these facets and propose concrete solutions that can be adopted by individuals, academic institutions, and society., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: One in three patients with epilepsy are medication-refractory and may benefit from investigations and operative treatment at a comprehensive epilepsy center. However, while these centers have capabilities for advanced seizure monitoring and surgical intervention, they are not required to have a functional neurosurgeon who is primarily focused in epilepsy surgery. Therefore, the objective of this study is to determine the impact of having a sub-specialized, epilepsy-focused functional neurosurgeon on patient outcomes., Methods: We conducted a retrospective chart review for all patients who underwent surgical intervention for medically refractory epilepsy at a Level 4 comprehensive Epilepsy Center from 2008 through 2019. Data was divided into two groups: group 1 comprised patients who had surgery before the hiring of a dedicated epilepsy-focused functional neurosurgeon in 2016, and group 2 was afterwards. We compared surgical procedures, significant complications, and seizure outcomes., Results: A total of 101 patients underwent 105 operations (52 in group 1 and 53 in group 2), not including intracranial EEG insertion. Compared to group 1, group 2 had more surgeries performed per year (15.1 vs. 6.5), and a significantly lower Engel score at last follow-up (1.78 vs. 2.57; p < 0.001). There was no difference in percentage of cases undergoing iEEG, and no difference in complication rates., Conclusions: In this series, the hiring of a sub-specialized functional neurosurgeon dedicated to epilepsy surgery in a comprehensive epilepsy center was associated with an increase in surgical volume and improved seizure outcomes., (Crown Copyright © 2021. Published by Elsevier B.V. All rights reserved.)

Background: Stereotactic electroencephalography (SEEG) has largely become the preferred method for intracranial seizure localization in epileptic patients due to its low morbidity and minimally invasive approach. While robotic placement is gaining popularity, many centers continue to use manual frame-based and frameless methods for electrode insertion. However, it is unclear how these methods compare in regard to accuracy, precision, and safety. Here, we aim to compare frame-based insertion using a CRW frame (Integra®) and frameless insertion using the StealthStation™ S7 (Medtronic®) navigation system for common temporal SEEG targets., Methods: We retrospectively examined electrode targets in SEEG patients that were implanted with either frame-based or frameless methods at a level 4 epilepsy center. We focused on two commonly used targets: amygdala and hippocampal head. Stealth station software was used to merge pre-operative MR with post-operative CT images for each patient, and coordinates for each electrode tip were calculated in relation to the midcommissural point. These were compared to predetermined ideal coordinates in regard to error and directional bias., Results: A total of 81 SEEG electrodes were identified in 23 patients (40 amygdala and 41 hippocampal head). Eight of 45 electrodes (18%) placed with the frameless technique and 0 of 36 electrodes (0%) placed with the frame-based technique missed their target and were not clinically useful. The average Euclidean distance comparing actual to ideal electrode tip coordinates for frameless vs. frame-based techniques was 11.0 mm vs. 7.1 mm (p < 0.001) for the amygdala and 12.4 mm vs. 8.5 mm (p < 0.001) for the hippocampal head, respectively. There were no hemorrhages or clinical complications in either group., Conclusions: Based on this series, frame-based SEEG insertion is significantly more accurate and precise and results in more clinically useful electrode contacts, compared to frameless insertion using a navigation guidance system. This has important implications for centers not currently using robotic insertion.

Background: Deep brain stimulation (DBS) is an effective therapy for a variety of refractory movement disorders. Accurate lead placement in the target nucleus is critical to ensure therapeutic effects and to minimize side effects, and intraoperative computed tomography (iCT) scan has been used to target and confirm lead position. The objective of this study is to compare the accuracy of determining the x, y, and z coordinates of final lead placement using iCT scan relative to postoperative magnetic resonance imaging (MRI)., Methods: We conducted a retrospective study on 83 patients who underwent insertion of 145 DBS leads from 2015 to 2017 at a single institution. iCT scan was merged with the preoperative MRI to determine lead coordinates on both magnetic resonance and computed tomography images independently, and the absolute differences between the x, y, and z coordinates between the 2 scans along with the Euclidean vectors were calculated., Results: The mean absolute differences ± standard error of the mean between iCT scan and postoperative MRI coordinates were as follows: x = 0.01 ± 0.09 mm (P = 0.89), y = 1.67 ± 0.14 mm (P < 0.001), and z = 2.75 ± 0.15 mm (P < 0.001). The average Euclidean vector difference was 3.21 ± 0.15 mm (P < 0.001)., Conclusions: Significant differences exist between iCT scan and postoperative MRI DBS y and z lead coordinates, but not with x coordinates. Based on this series, iCT scan is more accurate when confirming x coordinates, and less accurate for confirming y and z coordinates during DBS operations., (Crown Copyright © 2020. Published by Elsevier Inc. All rights reserved.)

Purpose: Oral squamous cell carcinoma (OSCC) is a highly prevalent type of immunogenic cancer with a low survival rate in patients with comorbidities owing to toxic habits., Materials and Methods: A retrospective cohort study was conducted of patients with resectable OSCC at a tertiary Spanish hospital from 2011 to 2014. The primary predictor variables were comorbidity and immune biomarkers. Comorbidity was assessed using the Adult Comorbidity Evaluation-27 (ACE-27) and scored from 1 to 3 (mild to severe decompensation, respectively). The immune biomarkers were neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR). The primary outcome variable was 5-year overall survival (OS). Other study variables were stage, margin, and neck management. Receiver operating characteristic curves were built for each ratio. For the survey of immune biomarkers, area under the curve was computed to determine cutoff points and investigate their association with OS. Kaplan-Meier estimates of survival and Cox proportional hazards models were used for longitudinal analysis., Results: Overall 215 patients were identified (median age, 67 yr; range, 32 to 96 yr; median follow-up, 31 months; range, 7 to 78 months); 159 patients had at least 1 comorbid condition. Results showed that a severe comorbidity (according to the ACE-27) increased the risk of death by 4 times in patients with OSCC regardless of stage. NLR, dNLR, LMR, and PLR were associated with OS in the univariate study. Cutoff points to predict increased mortality were 3, 1.9, 2.6, and 66 for NLR, dNLR, LMR, and PLR, respectively. Age, comorbidity, stage, margins, and management of the neck were important independent predictors of decreased OS in OSCC. PLR was marginally associated with OS in the multivariate model., Conclusion: These results suggest that comorbidity and NLR, dNLR, LMR, and PLR are associated with 5-year OS in patients with resectable OSCC., (Copyright © 2019 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.)

Despite decades of research, our understanding of epilepsy, including how seizures are generated and propagate, is incomplete. However, there is growing recognition that epilepsy is more than just the occurrence of seizures, with patients often experiencing comorbid deficits in cognition that are poorly understood. In addition, the available therapies for treatment of epilepsy, from pharmaceutical treatment to surgical resection and seizure prevention devices, often exacerbate deficits in cognitive function. In this review, we discuss the hypothesis that seizure generation and cognitive deficits have a similar pathological source characterized by, but not limited to, deficits in theta oscillations and their influence on interneurons. We present a new framework that describes oscillatory states in epilepsy as alternating between hyper- and hypo-synchrony rather than solely the spontaneous transition to hyper-excitability characterized by the seizures. This framework suggests that as neural oscillations, specifically in the theta range, vary their tempo from a slowed almost adagio tempo during interictal periods to faster, more rhythmic allegretto tempo preictally, they impact the function of interneurons, modulating their ability to control seizures and their role in cognitive processing. This slow wave oscillatory framework may help explain why current therapies that work to reduce hyper-excitability do not completely eliminate seizures and often lead to exacerbated cognitive deficits., (Copyright © 2019. Published by Elsevier Inc.)

Brain-machine interface-once the stuff of science fiction novels-is coming to a computer near you. The only question is: How soon? While the technology is in its infancy, it is already helping people with spinal cord injuries. Our authors examine its potential to be the ultimate game changer for any number of neurodegenerative diseases, as well as behavior, learning, and memory. They take the temperature of where the technology is, where it is going, and the inevitable ethical and regulatory implications ., (Copyright 2019 The Dana Foundation All Rights Reserved.)

Human orbitofrontal cortex (OFC) has long been implicated in value-based decision making. In recent years, convergent evidence from human and model organisms has further elucidated its role in representing reward-related computations underlying decision making. However, a detailed description of these processes remains elusive due in part to (1) limitations in our ability to observe human OFC neural dynamics at the timescale of decision processes and (2) methodological and interspecies differences that make it challenging to connect human and animal findings or to resolve discrepancies when they arise. Here, we sought to address these challenges by conducting multi-electrode electrocorticography (ECoG) recordings in neurosurgical patients during economic decision making to elucidate the electrophysiological signature, sub-second temporal profile, and anatomical distribution of reward-related computations within human OFC. We found that high-frequency activity (HFA) (70-200 Hz) reflected multiple valuation components grouped in two classes of valuation signals that were dissociable in temporal profile and information content: (1) fast, transient responses reflecting signals associated with choice and outcome processing, including anticipated risk and outcome regret, and (2) sustained responses explicitly encoding what happened in the immediately preceding trial. Anatomically, these responses were widely distributed in partially overlapping networks, including regions in the central OFC (Brodmann areas 11 and 13), which have been consistently implicated in reward processing in animal single-unit studies. Together, these results integrate insights drawn from human and animal studies and provide evidence for a role of human OFC in representing multiple reward computations., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Human intracranial electroencephalography (iEEG) recordings provide data with much greater spatiotemporal precision than is possible from data obtained using scalp EEG, magnetoencephalography (MEG), or functional MRI. Until recently, the fusion of anatomical data (MRI and computed tomography (CT) images) with electrophysiological data and their subsequent analysis have required the use of technologically and conceptually challenging combinations of software. Here, we describe a comprehensive protocol that enables complex raw human iEEG data to be converted into more readily comprehensible illustrative representations. The protocol uses an open-source toolbox for electrophysiological data analysis (FieldTrip). This allows iEEG researchers to build on a continuously growing body of scriptable and reproducible analysis methods that, over the past decade, have been developed and used by a large research community. In this protocol, we describe how to analyze complex iEEG datasets by providing an intuitive and rapid approach that can handle both neuroanatomical information and large electrophysiological datasets. We provide a worked example using an example dataset. We also explain how to automate the protocol and adjust the settings to enable analysis of iEEG datasets with other characteristics. The protocol can be implemented by a graduate student or postdoctoral fellow with minimal MATLAB experience and takes approximately an hour to execute, excluding the automated cortical surface extraction.

The role of serotonin in human brain function remains elusive due, at least in part, to our inability to measure rapidly the local concentration of this neurotransmitter. We used fast-scan cyclic voltammetry to infer serotonergic signaling from the striatum of 14 brains of human patients with Parkinson's disease. Here we report these novel measurements and show that they correlate with outcomes and decisions in a sequential investment game. We find that serotonergic concentrations transiently increase as a whole following negative reward prediction errors, while reversing when counterfactual losses predominate. This provides initial evidence that the serotonergic system acts as an opponent to dopamine signaling, as anticipated by theoretical models. Serotonin transients on one trial were also associated with actions on the next trial in a manner that correlated with decreased exposure to poor outcomes. Thus, the fluctuations observed for serotonin appear to correlate with the inhibition of over-reactions and promote persistence of ongoing strategies in the face of short-term environmental changes. Together these findings elucidate a role for serotonin in the striatum, suggesting it encodes a protective action strategy that mitigates risk and modulates choice selection particularly following negative environmental events.

The habenula is a hub for cognitive and emotional signals that are relayed to the aminergic centers in the midbrain and, thus, plays an important role in goal-oriented behaviors. Although it is well described in rodents and non-human primates, the habenula functional network remains relatively uncharacterized in humans, partly because of the methodological challenges associated with the functional magnetic resonance imaging of small structures in the brain. Using high-resolution cardiac-gated resting state imaging in healthy humans and precisely identifying each participants' habenula, we show that the habenula is functionally coupled with the insula, parahippocampus, thalamus, periaqueductal grey, pons, striatum and substantia nigra/ventral tegmental area complex. Furthermore, by separately examining and comparing the functional maps from the left and right habenula, we provide the first evidence of an asymmetry in the functional connectivity of the habenula in humans. Hum Brain Mapp 37:2602-2615, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc., (© 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.)

Layer 4 (L4) of primary visual cortex (V1) is the main recipient of thalamocortical fibers from the dorsal lateral geniculate nucleus (LGNd). Thus, it is considered the main entry point of visual information into the neocortex and the first anatomical opportunity for intracortical visual processing before information leaves L4 and reaches supra- and infragranular cortical layers. The strength of monosynaptic connections from individual L4 excitatory cells onto adjacent L4 cells (unitary connections) is highly malleable, demonstrating that the initial stage of intracortical synaptic transmission of thalamocortical information can be altered by previous activity. However, the inhibitory network within L4 of V1 may act as an internal gate for induction of excitatory synaptic plasticity, thus providing either high fidelity throughput to supragranular layers or transmittal of a modified signal subject to recent activity-dependent plasticity. To evaluate this possibility, we compared the induction of synaptic plasticity using classical extracellular stimulation protocols that recruit a combination of excitatory and inhibitory synapses with stimulation of a single excitatory neuron onto a L4 cell. In order to induce plasticity, we paired pre- and postsynaptic activity (with the onset of postsynaptic spiking leading the presynaptic activation by 10ms) using extracellular stimulation (ECS) in acute slices of primary visual cortex and comparing the outcomes with our previously published results in which an identical protocol was used to induce synaptic plasticity between individual pre- and postsynaptic L4 excitatory neurons. Our results indicate that pairing of ECS with spiking in a L4 neuron fails to induce plasticity in L4-L4 connections if synaptic inhibition is intact. However, application of a similar pairing protocol under GABAARs inhibition by bath application of 2μM bicuculline does induce robust synaptic plasticity, long term potentiation (LTP) or long term depression (LTD), similar to our results with pairing of pre- and postsynaptic activation between individual excitatory L4 neurons in which inhibitory connections are not activated. These results are consistent with the well-established observation that inhibition limits the capacity for induction of plasticity at excitatory synapses and that pre- and postsynaptic activation at a fixed time interval can result in a variable range of plasticity outcomes. However, in the current study by virtue of having two sets of experimental data, we have provided a new insight into these processes. By randomly mixing the assorting of individual L4 neurons according to the frequency distribution of the experimentally determined plasticity outcome distribution based on the calculated convergence of multiple individual L4 neurons onto a single postsynaptic L4 neuron, we were able to compare then actual ECS plasticity outcomes to those predicted by randomly mixing individual pairs of neurons. Interestingly, the observed plasticity profiles with ECS cannot account for the random assortment of plasticity behaviors of synaptic connections between individual cell pairs. These results suggest that connections impinging onto a single postsynaptic cell may be grouped according to plasticity states.

In the mammalian brain, dopamine is a critical neuromodulator whose actions underlie learning, decision-making, and behavioral control. Degeneration of dopamine neurons causes Parkinson's disease, whereas dysregulation of dopamine signaling is believed to contribute to psychiatric conditions such as schizophrenia, addiction, and depression. Experiments in animal models suggest the hypothesis that dopamine release in human striatum encodes reward prediction errors (RPEs) (the difference between actual and expected outcomes) during ongoing decision-making. Blood oxygen level-dependent (BOLD) imaging experiments in humans support the idea that RPEs are tracked in the striatum; however, BOLD measurements cannot be used to infer the action of any one specific neurotransmitter. We monitored dopamine levels with subsecond temporal resolution in humans (n = 17) with Parkinson's disease while they executed a sequential decision-making task. Participants placed bets and experienced monetary gains or losses. Dopamine fluctuations in the striatum fail to encode RPEs, as anticipated by a large body of work in model organisms. Instead, subsecond dopamine fluctuations encode an integration of RPEs with counterfactual prediction errors, the latter defined by how much better or worse the experienced outcome could have been. How dopamine fluctuations combine the actual and counterfactual is unknown. One possibility is that this process is the normal behavior of reward processing dopamine neurons, which previously had not been tested by experiments in animal models. Alternatively, this superposition of error terms may result from an additional yet-to-be-identified subclass of dopamine neurons.

Connecting neural mechanisms of behavior to their underlying molecular and genetic substrates has important scientific and clinical implications. However, despite rapid growth in our knowledge of the functions and computational properties of neural circuitry underlying behavior in a number of important domains, there has been much less progress in extending this understanding to their molecular and genetic substrates, even in an age marked by exploding availability of genomic data. Here we describe recent advances in analytical strategies that aim to overcome two important challenges associated with studying the complex relationship between genes and behavior: (i) reducing distal behavioral phenotypes to a set of molecular, physiological, and neural processes that render them closer to the actions of genetic forces, and (ii) striking a balance between the competing demands of discovery and interpretability when dealing with genomic data containing up to millions of markers. Our proposed approach involves linking, on one hand, models of neural computations and circuits hypothesized to underlie behavior, and on the other hand, the set of the genes carrying out biochemical processes related to the functioning of these neural systems. In particular, we focus on the specific example of value-based decision-making, and discuss how such a combination allows researchers to leverage existing biological knowledge at both neural and genetic levels to advance our understanding of the neurogenetic mechanisms underlying behavior.

Game theory describes strategic interactions where success of players' actions depends on those of coplayers. In humans, substantial progress has been made at the neural level in characterizing the dopaminergic and frontostriatal mechanisms mediating such behavior. Here we combined computational modeling of strategic learning with a pathway approach to characterize association of strategic behavior with variations in the dopamine pathway. Specifically, using gene-set analysis, we systematically examined contribution of different dopamine genes to variation in a multistrategy competitive game captured by (i) the degree players anticipate and respond to actions of others (belief learning) and (ii) the speed with which such adaptations take place (learning rate). We found that variation in genes that primarily regulate prefrontal dopamine clearance--catechol-O-methyl transferase (COMT) and two isoforms of monoamine oxidase--modulated degree of belief learning across individuals. In contrast, we did not find significant association for other genes in the dopamine pathway. Furthermore, variation in genes that primarily regulate striatal dopamine function--dopamine transporter and D2 receptors--was significantly associated with the learning rate. We found that this was also the case with COMT, but not for other dopaminergic genes. Together, these findings highlight dissociable roles of frontostriatal systems in strategic learning and support the notion that genetic variation, organized along specific pathways, forms an important source of variation in complex phenotypes such as strategic behavior.

Angioplasty has long been used in the treatment of peripheral arterial occlusive disease with variable long-term results. In this case report, we present a patient with marfanoid features and acute ischemia of the lower extremity. Angioplasty provided us with the means of emergently relieving the acute symptoms. The patient was subsequently found on further work-up to have hyperhomocysteinemia (HC) and appropriate medical therapy was initiated. We conclude that angioplasty should be considered in pediatric patients with acute occlusive limb ischemia, providing excellent immediate results to preserve the limb as well as the time to investigate the underlying causes.