scholarly journals Multivariate Stochastic Volatility Modeling of Neural Data

2018 ◽  
Author(s):  
Tung D. Phan ◽  
Jessica A. Wacther ◽  
Ethan A. Solomon ◽  
Michael J. Kahana
Keyword(s):  
Latent Variable ◽  
Medial Temporal Lobe ◽  
Implied Volatility ◽  
Brain Regions ◽  
Neural Signals ◽  
Neurosurgical Patients ◽  
Multivariate Stochastic Volatility ◽  
Multivariate Autoregressive Models ◽  
Brain And Behavior ◽  
And Behavior

AbstractBecause multivariate autoregressive models have failed to adequately account for the complexity of neural signals, researchers have predominantly relied on non-parametric methods when studying the relations between brain and behavior. Using medial temporal lobe (MTL) recordings from 96 neurosurgical patients, we show that time series models with volatility described by a multivariate stochastic latent-variable process and lagged interactions between signals in different brain regions provide new insights into the dynamics of brain function. The implied volatility inferred from our process positively correlates with high-frequency spectral activity, a signal that correlates with neuronal activity. We show that volatility features derived from our model can reliably decode memory states, and that this classifier performs as well as those using spectral features. Using the directional connections between brain regions during complex cognitive process provided by the model, we uncovered perirhinal-hippocampal desynchronization in the MTL regions that is associated with successful memory encoding.

scholarly journals Multivariate stochastic volatility modeling of neural data

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Tung D Phan ◽  
Jessica A Wachter ◽  
Ethan A Solomon ◽  
Michael J Kahana
Keyword(s):  
Latent Variable ◽  
Medial Temporal Lobe ◽  
Implied Volatility ◽  
Brain Regions ◽  
Neural Signals ◽  
Neurosurgical Patients ◽  
Multivariate Stochastic Volatility ◽  
Multivariate Autoregressive Models ◽  
Brain And Behavior ◽  
And Behavior

Because multivariate autoregressive models have failed to adequately account for the complexity of neural signals, researchers have predominantly relied on non-parametric methods when studying the relations between brain and behavior. Using medial temporal lobe (MTL) recordings from 96 neurosurgical patients, we show that time series models with volatility described by a multivariate stochastic latent-variable process and lagged interactions between signals in different brain regions provide new insights into the dynamics of brain function. The implied volatility inferred from our process positively correlates with high-frequency spectral activity, a signal that correlates with neuronal activity. We show that volatility features derived from our model can reliably decode memory states, and that this classifier performs as well as those using spectral features. Using the directional connections between brain regions during complex cognitive process provided by the model, we uncovered perirhinal-hippocampal desynchronization in the MTL regions that is associated with successful memory encoding.

scholarly journals AMPed-up adolescents: the role of age in the abuse of amphetamines and its consequences on cognition and prefrontal cortex development

2020 ◽  
Author(s):  
Sara Ruth Westbrook ◽  
Lauren Carrica ◽  
Asia Banks ◽  
Joshua Michael Gulley
Keyword(s):  
Prefrontal Cortex ◽  
Animal Studies ◽  
Drug Effects ◽  
Epidemiological Studies ◽  
Brain Regions ◽  
Vulnerability Factors ◽  
Brain And Behavior ◽  
And Behavior ◽  
Detrimental Impact

Adolescent use of amphetamine and its closely related, methylated version methamphetamine, is alarmingly high in those who use drugs for nonmedical purposes. This raises serious concerns about the potential for this drug use to have a long-lasting, detrimental impact on the normal development of the brain and behavior that is ongoing during adolescence. In this review, we explore recent findings from both human and laboratory animal studies that investigate the consequences of amphetamine and methamphetamine exposure during this stage of life. We highlight studies that assess sex differences in adolescence, as well as those that are designed specifically to address the potential unique effects of adolescent exposure by including groups at other life stages (typically young adulthood). We consider epidemiological studies on age and sex as vulnerability factors for developing problems with the use of amphetamines, as well as human and animal laboratory studies that tap into age differences in use, its short-term effects on behavior, and the long-lasting consequences of this exposure on cognition. We also focus on studies of drug effects in the prefrontal cortex, which is known to be critically important for cognition and is among the later maturing brain regions. Finally, we discuss important issues that should be addressed in future studies so that the field can further our understanding of the mechanisms underlying adolescent use of amphetamines and its outcomes on the developing brain and behavior.

Oxytocin and Vasopressin: Mechanisms for Potential Sex Differences Observed in Autism Spectrum Disorders

2013 ◽  
Author(s):  
C. Sue Carter ◽  
Suma Jacob
Keyword(s):  
Autism Spectrum Disorders ◽  
Arginine Vasopressin ◽  
Protective Factor ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Sexually Dimorphic ◽  
Unique Role ◽  
Spectrum Disorders ◽  
Brain And Behavior ◽  
And Behavior

The effects of oxytocin and vasopressin on the brain and behavior can be sexually dimorphic, especially during the course of development (Bales, Kim, et al., 2004; Bales, Pfeifer, et al., 2004; Bales, Plotsky, et al., 2007; Bielsky et al., 2005a; Carter, 2003; Thompson et al., 2006; Yamamoto et al., 2005; Yamamoto et al., 2004). Given the sexual discrepancy observed in autism spectrum disorders (ASDs), these two neuropeptides, oxytocin (OT) and arginine vasopressin (AVP), have received attention for their potential role in ASDs (Green and Hollander, 2010; Insel et al., 1999; Leckman & Herman, 2002; Welch et al., 2005; Winslow, 2005; Young et al., 2002). Changes in either OT or AVP and their receptors could be capable of influencing symptom domains or behaviors associated with ASDs. Arginine vasopressin is androgen dependent in some brain regions (De Vries & Panzica, 2006), and males are more sensitive to AVP, especially during development. We hypothesize here that AVP, which has a unique role in males, must be present in optimal levels to be protective against ASDs. Either excess AVP or disruptions in the AVP system could play a role in development of the traits found in ASDs. In contrast, OT may possibly be secreted in response to adversity, especially in females, serving as a protective factor.

scholarly journals Gaussian Process Linking Functions for Mind, Brain and Behavior

2019 ◽  
Author(s):  
Giwon Bahg ◽  
Daniel G. Evans ◽  
Matthew Galdo ◽  
Brandon Turner
Keyword(s):  
Simulation Study ◽  
Latent Variable ◽  
Predictive Accuracy ◽  
Temporal Structure ◽  
Behavioral Data ◽  
Inference Procedure ◽  
Brain And Behavior ◽  
The Mind ◽  
And Behavior ◽  
The Brain

The link between mind, brain, and behavior has mystified philosophers and scientists for millennia. Recent progress has been made by forming statistical associations between manifest variables of the brain (e.g., EEG, fMRI) and manifest variables of behavior (e.g., response times, accuracy) through hierarchical latent variable models (Turner, Forstmann, & Steyvers, 2019). Within this framework, one can make inferences about the mind in a statistically principled way, such that complex patterns of brain-behavior associations drive the inference procedure. However, previous approaches were limited in the flexibility of the linking function, which has proven prohibitive for understanding the complex dynamics exhibited by the brain. In this article, we propose a data-driven, non-parametric approach that allows complex linking functions to emerge from fitting a hierarchical latent representation of the mind to multivariate, multimodal data. Furthermore, to enforce biological plausibility, we impose both spatial and temporal structure so that the types of realizable system dynamics are constrained. To illustrate the benefits of our approach, we investigate the model’s performance in a simulation study and apply it to experimental data. In the simulation study, we verify that the model can be accurately fit to simulated data, and latent dynamics can be well recovered. In an experimental application, we simultaneously fit the model to fMRI and behavioral data from a continuous motion tracking task. We show that the model accurately recovers both neural and behavioral data, and reveals interesting latent cognitive dynamics. Finally, we provide a test of the model’s generalizability by assessing its predictive accuracy in a cross-validation test.

scholarly journals Gaussian process linking functions for mind, brain, and behavior

2020 ◽  
Vol 117 (47) ◽  
pp. 29398-29406 ◽  
Author(s):  
Giwon Bahg ◽  
Daniel G. Evans ◽  
Matthew Galdo ◽  
Brandon M. Turner
Keyword(s):  
Simulation Study ◽  
Latent Variable ◽  
Temporal Structure ◽  
Simulated Data ◽  
Behavioral Data ◽  
Inference Procedure ◽  
Brain And Behavior ◽  
The Mind ◽  
And Behavior ◽  
The Brain

The link between mind, brain, and behavior has mystified philosophers and scientists for millennia. Recent progress has been made by forming statistical associations between manifest variables of the brain (e.g., electroencephalogram [EEG], functional MRI [fMRI]) and manifest variables of behavior (e.g., response times, accuracy) through hierarchical latent variable models. Within this framework, one can make inferences about the mind in a statistically principled way, such that complex patterns of brain–behavior associations drive the inference procedure. However, previous approaches were limited in the flexibility of the linking function, which has proved prohibitive for understanding the complex dynamics exhibited by the brain. In this article, we propose a data-driven, nonparametric approach that allows complex linking functions to emerge from fitting a hierarchical latent representation of the mind to multivariate, multimodal data. Furthermore, to enforce biological plausibility, we impose both spatial and temporal structure so that the types of realizable system dynamics are constrained. To illustrate the benefits of our approach, we investigate the model’s performance in a simulation study and apply it to experimental data. In the simulation study, we verify that the model can be accurately fitted to simulated data, and latent dynamics can be well recovered. In an experimental application, we simultaneously fit the model to fMRI and behavioral data from a continuous motion tracking task. We show that the model accurately recovers both neural and behavioral data and reveals interesting latent cognitive dynamics, the topology of which can be contrasted with several aspects of the experiment.

scholarly journals Mouse brain-wide mitochondrial connectivity anchored in gene, brain and behavior

2021 ◽  
Author(s):  
Ayelet Rosenberg ◽  
Manish Saggar ◽  
Peter Rogu ◽  
Aaron W. Limoges ◽  
Carmen Sandi ◽  
...  
Keyword(s):  
Large Scale ◽  
Functional Organization ◽  
Production Capacity ◽  
Mitochondrial Respiratory Chain ◽  
Brain Regions ◽  
Wide Scale ◽  
Brain And Behavior ◽  
Large Scale Networks ◽  
And Behavior ◽  
Multimodal Evidence

AbstractThe brain and behavior are under energetic constraints, which are likely driven by mitochondrial energy production capacity. However, the mitochondria-behavior relationship has not been systematically studied on a brain-wide scale. Here we examine the association between mitochondrial health index and stress-related behaviors in mice with diverse mitochondrial and behavioral phenotypes. Miniaturized assays of mitochondrial respiratory chain function and mitochondrial DNA (mtDNA) content were deployed on 571 samples from 17 brain regions. We find specific patterns of mito-behavior associations that vary across brain regions and behaviors. Furthermore, multi-slice network analysis applied to our brain-wide mitochondrial dataset identified three large-scale networks of brain regions. A major network composed of cortico-striatal regions exhibits highest mitochondria-behavior correlations, suggesting that this mito-based network is functionally significant. Mito-based networks can also be recapitulated using correlated gene expression and structural connectome data, thereby providing convergent multimodal evidence of mitochondrial functional organization anchored in gene, brain and behavior.

scholarly journals Whole-cortex mapping of common genetic influences on depression and a social deficits dimension

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Alexander S. Hatoum ◽  
Andrew E. Reineberg ◽  
Harry R. Smolker ◽  
John K. Hewitt ◽  
Naomi P. Friedman
Keyword(s):  
High Resolution ◽  
Brain Regions ◽  
Posterior Cingulate Cortex ◽  
Genetic Vulnerability ◽  
Downstream Effects ◽  
Distributed Process ◽  
Brain And Behavior ◽  
Longitudinal Twin Study ◽  
The Right ◽  
And Behavior

AbstractSocial processes are associated with depression, particularly understanding and responding to others, deficits in which can manifest as callousness/unemotionality (CU). Thus, CU may reflect some of the genetic risk to depression. Further, this vulnerability likely reflects the neurological substrates of depression, presenting biomarkers to capture genetic vulnerability of depression severity. However, heritability varies within brain regions, so a high-resolution genetic perspective is needed. We developed a toolbox that maps genetic and environmental associations between brain and behavior at high resolution. We used this toolbox to estimate brain areas that are genetically associated with both depressive symptoms and CU in a sample of 258 same-sex twin pairs from the Colorado Longitudinal Twin Study (LTS). We then overlapped the two maps to generate coordinates that allow for tests of downstream effects of genes influencing our clusters. Genetic variance influencing cortical thickness in the right dorsal lateral prefrontal cortex (DLFPC) sulci and gyri, ventral posterior cingulate cortex (PCC), pre-somatic motor cortex (PreSMA), medial precuneus, left occipital-temporal junction (OTJ), parietal–temporal junction (PTJ), ventral somatosensory cortex (vSMA), and medial and lateral precuneus were genetically associated with both depression and CU. Split-half replication found support for both DLPFC clusters. Meta-analytic term search identified “theory of mind”, “inhibit”, and “pain” as likely functions. Gene and transcript mapping/enrichment analyses implicated calcium channels. CU reflects genetic vulnerability to depression that likely involves executive and social functioning in a distributed process across the cortex. This approach works to unify neuroimaging, neuroinformatics, and genetics to discover pathways to psychiatric vulnerability.

scholarly journals Post-weaning Social Isolation in Male and Female Prairie Voles: Impacts on Central and Peripheral Immune System

2022 ◽  
Vol 15 ◽  
Author(s):  
Meghan L. Donovan ◽  
Eileen K. Chun ◽  
Yan Liu ◽  
Zuoxin Wang
Keyword(s):  
Immune System ◽  
Social Isolation ◽  
Forced Swim Test ◽  
Brain Regions ◽  
Prairie Voles ◽  
Male And Female ◽  
Bed Nucleus ◽  
Brain And Behavior ◽  
And Behavior ◽  
The Brain

The socially monogamous prairie vole (Microtus ochrogaster) offers a unique opportunity to examine the impacts of adolescent social isolation on the brain, immune system, and behavior. In the current study, male and female prairie voles were randomly assigned to be housed alone or with a same-sex cagemate after weaning (i.e., on postnatal day 21–22) for a 6-week period. Thereafter, subjects were tested for anxiety-like and depressive-like behaviors using the elevated plus maze (EPM) and Forced Swim Test (FST), respectively. Blood was collected to measure peripheral cytokine levels, and brain tissue was processed for microglial density in various brain regions, including the Nucleus Accumbens (NAcc), Medial Amygdala (MeA), Central Amygdala (CeA), Bed Nucleus of the Stria Terminalis (BNST), and Paraventricular Nucleus of the Hypothalamus (PVN). Sex differences were found in EPM and FST behaviors, where male voles had significantly lower total arm entries in the EPM as well as lower latency to immobility in the FST compared to females. A sex by treatment effect was found in peripheral IL-1β levels, where isolated males had a lower level of IL-1β compared to cohoused females. Post-weaning social isolation also altered microglial density in a brain region-specific manner. Isolated voles had higher microglial density in the NAcc, MeA, and CeA, but lower microglial density in the dorsal BNST. Cohoused male voles also had higher microglial density in the PVN compared to cohoused females. Taken together, these data suggest that post-weaning social housing environments can alter peripheral and central immune systems in prairie voles, highlighting a potential role for the immune system in shaping isolation-induced alterations to the brain and behavior.

scholarly journals Whole-Cortex Mapping of Common Genetic Influences on Depression and Social Deficits

2018 ◽  
Author(s):  
Alexander S. Hatoum ◽  
Andrew E. Reinberg ◽  
Harry R. Smolker ◽  
John K. Hewitt ◽  
Naomi P. Friedman
Keyword(s):  
High Resolution ◽  
Brain Regions ◽  
Posterior Cingulate Cortex ◽  
Genetic Vulnerability ◽  
Downstream Effects ◽  
Distributed Process ◽  
Brain And Behavior ◽  
Longitudinal Twin Study ◽  
The Right ◽  
And Behavior

AbstractBackgroundSocial processes are associated with depression, particularly understanding and responding to others, deficits in which can manifest as callousness/unemotionality (CU). Thus, CU may reflect some of the genetic risk to depression. Further, this vulnerability likely reflects the neurological substrates of depression, presenting biomarkers to capture genetic vulnerability of depression severity. However, heritability varies within brain regions, so a high-resolution genetic perspective is needed.Method In a sample of 258 same-sex twin pairs from the Colorado Longitudinal Twin Study (LTS), we developed a toolbox that maps genetic and environmental associations between brain and behavior at high resolution. We used this toolbox to estimate brain areas that are genetically associated with both depressive symptoms and CU. We then overlapped the two maps to generate coordinates that allow for tests of downstream effects of genes influencing our clusters.Results Genetic variance influencing cortical thickness in the right dorsal lateral prefrontal cortex (DLFPC) sulci and gyri, ventral posterior cingulate cortex (PCC), pre-somatic motor cortex (PreSMA), medial precuneus, left occipital-temporal junction (OTJ), parietal-temporal junction (PTJ), ventral somatosensory cortex (vSMA), and medial and lateral precuneus were genetically associated with both depression and CU. Split-half replication found support for both DLPFC clusters. Meta-analytic term search identified “theory of mind”, “inhibit”, and “pain” as likely functions. Gene and transcript mapping/enrichment analyses implicated calcium channels.ConclusionsCU reflects genetic vulnerability to depression that likely involves executive and social functioning in a distributed process across the cortex. This approach works to unify neuroimaging, neuroinformatics, and genetics to discover pathways to psychiatric vulnerability.

Neuropsychiatry Looks at Man's Brain and Behavior

1959 ◽  
Vol 4 (1) ◽  
pp. 9-10
Author(s):  
LEONARD CARMICHAEL
Keyword(s):  
Brain And Behavior ◽  
And Behavior
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