ongoing neural activity: Topics by Science.gov

Sample records for ongoing neural activity

Stimuli Reduce the Dimensionality of Cortical Activity

PubMed Central

Mazzucato, Luca; Fontanini, Alfredo; La Camera, Giancarlo

2016-01-01

The activity of ensembles of simultaneously recorded neurons can be represented as a set of points in the space of firing rates. Even though the dimension of this space is equal to the ensemble size, neural activity can be effectively localized on smaller subspaces. The dimensionality of the neural space is an important determinant of the computational tasks supported by the neural activity. Here, we investigate the dimensionality of neural ensembles from the sensory cortex of alert rats during periods of ongoing (inter-trial) and stimulus-evoked activity. We find that dimensionality grows linearly with ensemble size, and grows significantly faster during ongoing activity compared to evoked activity. We explain these results using a spiking network model based on a clustered architecture. The model captures the difference in growth rate between ongoing and evoked activity and predicts a characteristic scaling with ensemble size that could be tested in high-density multi-electrode recordings. Moreover, we present a simple theory that predicts the existence of an upper bound on dimensionality. This upper bound is inversely proportional to the amount of pair-wise correlations and, compared to a homogeneous network without clusters, it is larger by a factor equal to the number of clusters. The empirical estimation of such bounds depends on the number and duration of trials and is well predicted by the theory. Together, these results provide a framework to analyze neural dimensionality in alert animals, its behavior under stimulus presentation, and its theoretical dependence on ensemble size, number of clusters, and correlations in spiking network models. PMID:26924968
Stimuli Reduce the Dimensionality of Cortical Activity.

PubMed

Mazzucato, Luca; Fontanini, Alfredo; La Camera, Giancarlo

2016-01-01

The activity of ensembles of simultaneously recorded neurons can be represented as a set of points in the space of firing rates. Even though the dimension of this space is equal to the ensemble size, neural activity can be effectively localized on smaller subspaces. The dimensionality of the neural space is an important determinant of the computational tasks supported by the neural activity. Here, we investigate the dimensionality of neural ensembles from the sensory cortex of alert rats during periods of ongoing (inter-trial) and stimulus-evoked activity. We find that dimensionality grows linearly with ensemble size, and grows significantly faster during ongoing activity compared to evoked activity. We explain these results using a spiking network model based on a clustered architecture. The model captures the difference in growth rate between ongoing and evoked activity and predicts a characteristic scaling with ensemble size that could be tested in high-density multi-electrode recordings. Moreover, we present a simple theory that predicts the existence of an upper bound on dimensionality. This upper bound is inversely proportional to the amount of pair-wise correlations and, compared to a homogeneous network without clusters, it is larger by a factor equal to the number of clusters. The empirical estimation of such bounds depends on the number and duration of trials and is well predicted by the theory. Together, these results provide a framework to analyze neural dimensionality in alert animals, its behavior under stimulus presentation, and its theoretical dependence on ensemble size, number of clusters, and correlations in spiking network models.
Critical Branching Neural Networks

ERIC Educational Resources Information Center

Kello, Christopher T.

2013-01-01

It is now well-established that intrinsic variations in human neural and behavioral activity tend to exhibit scaling laws in their fluctuations and distributions. The meaning of these scaling laws is an ongoing matter of debate between isolable causes versus pervasive causes. A spiking neural network model is presented that self-tunes to critical…
Weak correlations between hemodynamic signals and ongoing neural activity during the resting state

PubMed Central

Winder, Aaron T.; Echagarruga, Christina; Zhang, Qingguang; Drew, Patrick J.

2017-01-01

Spontaneous fluctuations in hemodynamic signals in the absence of a task or overt stimulation are used to infer neural activity. We tested this coupling by simultaneously measuring neural activity and changes in cerebral blood volume (CBV) in the somatosensory cortex of awake, head-fixed mice during periods of true rest, and during whisker stimulation and volitional whisking. Here we show that neurovascular coupling was similar across states, and large spontaneous CBV changes in the absence of sensory input were driven by volitional whisker and body movements. Hemodynamic signals during periods of rest were weakly correlated with neural activity. Spontaneous fluctuations in CBV and vessel diameter persisted when local neural spiking and glutamatergic input was blocked, and during blockade of noradrenergic receptors, suggesting a non-neuronal origin for spontaneous CBV fluctuations. Spontaneous hemodynamic signals reflect a combination of behavior, local neural activity, and putatively non-neural processes. PMID:29184204
Weak correlations between hemodynamic signals and ongoing neural activity during the resting state.

PubMed

Winder, Aaron T; Echagarruga, Christina; Zhang, Qingguang; Drew, Patrick J

2017-12-01

Spontaneous fluctuations in hemodynamic signals in the absence of a task or overt stimulation are used to infer neural activity. We tested this coupling by simultaneously measuring neural activity and changes in cerebral blood volume (CBV) in the somatosensory cortex of awake, head-fixed mice during periods of true rest and during whisker stimulation and volitional whisking. We found that neurovascular coupling was similar across states and that large, spontaneous CBV changes in the absence of sensory input were driven by volitional whisker and body movements. Hemodynamic signals during periods of rest were weakly correlated with neural activity. Spontaneous fluctuations in CBV and vessel diameter persisted when local neural spiking and glutamatergic input were blocked, as well as during blockade of noradrenergic receptors, suggesting a non-neuronal origin for spontaneous CBV fluctuations. Spontaneous hemodynamic signals reflect a combination of behavior, local neural activity, and putatively non-neural processes.
A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning.

PubMed

Kappel, David; Legenstein, Robert; Habenschuss, Stefan; Hsieh, Michael; Maass, Wolfgang

2018-01-01

Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is at least as large as the component that depends on the history of pre- and postsynaptic neural activity. These data are inconsistent with common models for network plasticity and raise the following questions: how can neural circuits maintain a stable computational function in spite of these continuously ongoing processes, and what could be functional uses of these ongoing processes? Here, we present a rigorous theoretical framework for these seemingly stochastic spine dynamics and rewiring processes in the context of reward-based learning tasks. We show that spontaneous synapse-autonomous processes, in combination with reward signals such as dopamine, can explain the capability of networks of neurons in the brain to configure themselves for specific computational tasks, and to compensate automatically for later changes in the network or task. Furthermore, we show theoretically and through computer simulations that stable computational performance is compatible with continuously ongoing synapse-autonomous changes. After reaching good computational performance it causes primarily a slow drift of network architecture and dynamics in task-irrelevant dimensions, as observed for neural activity in motor cortex and other areas. On the more abstract level of reinforcement learning the resulting model gives rise to an understanding of reward-driven network plasticity as continuous sampling of network configurations.
A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning

PubMed Central

Habenschuss, Stefan; Hsieh, Michael

2018-01-01

Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is at least as large as the component that depends on the history of pre- and postsynaptic neural activity. These data are inconsistent with common models for network plasticity and raise the following questions: how can neural circuits maintain a stable computational function in spite of these continuously ongoing processes, and what could be functional uses of these ongoing processes? Here, we present a rigorous theoretical framework for these seemingly stochastic spine dynamics and rewiring processes in the context of reward-based learning tasks. We show that spontaneous synapse-autonomous processes, in combination with reward signals such as dopamine, can explain the capability of networks of neurons in the brain to configure themselves for specific computational tasks, and to compensate automatically for later changes in the network or task. Furthermore, we show theoretically and through computer simulations that stable computational performance is compatible with continuously ongoing synapse-autonomous changes. After reaching good computational performance it causes primarily a slow drift of network architecture and dynamics in task-irrelevant dimensions, as observed for neural activity in motor cortex and other areas. On the more abstract level of reinforcement learning the resulting model gives rise to an understanding of reward-driven network plasticity as continuous sampling of network configurations. PMID:29696150
Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns

PubMed Central

Cruchet, Steeve; Gustafson, Kyle; Benton, Richard; Floreano, Dario

2015-01-01

The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs—locomotor bouts—matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior. PMID:26600381
Controlling Working Memory Operations by Selective Gating: The Roles of Oscillations and Synchrony

PubMed Central

Dipoppa, Mario; Szwed, Marcin; Gutkin, Boris S.

2016-01-01

Working memory (WM) is a primary cognitive function that corresponds to the ability to update, stably maintain, and manipulate short-term memory (ST M) rapidly to perform ongoing cognitive tasks. A prevalent neural substrate of WM coding is persistent neural activity, the property of neurons to remain active after having been activated by a transient sensory stimulus. This persistent activity allows for online maintenance of memory as well as its active manipulation necessary for task performance. WM is tightly capacity limited. Therefore, selective gating of sensory and internally generated information is crucial for WM function. While the exact neural substrate of selective gating remains unclear, increasing evidence suggests that it might be controlled by modulating ongoing oscillatory brain activity. Here, we review experiments and models that linked selective gating, persistent activity, and brain oscillations, putting them in the more general mechanistic context of WM. We do so by defining several operations necessary for successful WM function and then discussing how such operations may be carried out by mechanisms suggested by computational models. We specifically show how oscillatory mechanisms may provide a rapid and flexible active gating mechanism for WM operations. PMID:28154616
Controlling Working Memory Operations by Selective Gating: The Roles of Oscillations and Synchrony.

PubMed

Dipoppa, Mario; Szwed, Marcin; Gutkin, Boris S

2016-01-01

Working memory (WM) is a primary cognitive function that corresponds to the ability to update, stably maintain, and manipulate short-term memory (ST M) rapidly to perform ongoing cognitive tasks. A prevalent neural substrate of WM coding is persistent neural activity , the property of neurons to remain active after having been activated by a transient sensory stimulus. This persistent activity allows for online maintenance of memory as well as its active manipulation necessary for task performance. WM is tightly capacity limited. Therefore, selective gating of sensory and internally generated information is crucial for WM function. While the exact neural substrate of selective gating remains unclear, increasing evidence suggests that it might be controlled by modulating ongoing oscillatory brain activity. Here, we review experiments and models that linked selective gating, persistent activity, and brain oscillations, putting them in the more general mechanistic context of WM. We do so by defining several operations necessary for successful WM function and then discussing how such operations may be carried out by mechanisms suggested by computational models. We specifically show how oscillatory mechanisms may provide a rapid and flexible active gating mechanism for WM operations.
I think therefore I am: Rest-related prefrontal cortex neural activity is involved in generating the sense of self.

PubMed

Gruberger, M; Levkovitz, Y; Hendler, T; Harel, E V; Harari, H; Ben Simon, E; Sharon, H; Zangen, A

2015-05-01

The sense of self has always been a major focus in the psychophysical debate. It has been argued that this complex ongoing internal sense cannot be explained by any physical measure and therefore substantiates a mind-body differentiation. Recently, however, neuro-imaging studies have associated self-referential spontaneous thought, a core-element of the ongoing sense of self, with synchronous neural activations during rest in the medial prefrontal cortex (PFC), as well as the medial and lateral parietal cortices. By applying deep transcranial magnetic stimulation (TMS) over human PFC before rest, we disrupted activity in this neural circuitry thereby inducing reports of lowered self-awareness and strong feelings of dissociation. This effect was not found with standard or sham TMS, or when stimulation was followed by a task instead of rest. These findings demonstrate for the first time a critical, causal role of intact rest-related PFC activity patterns in enabling integrated, enduring, self-referential mental processing. Copyright © 2015 Elsevier Inc. All rights reserved.
Parametric models to relate spike train and LFP dynamics with neural information processing.

PubMed

Banerjee, Arpan; Dean, Heather L; Pesaran, Bijan

2012-01-01

Spike trains and local field potentials (LFPs) resulting from extracellular current flows provide a substrate for neural information processing. Understanding the neural code from simultaneous spike-field recordings and subsequent decoding of information processing events will have widespread applications. One way to demonstrate an understanding of the neural code, with particular advantages for the development of applications, is to formulate a parametric statistical model of neural activity and its covariates. Here, we propose a set of parametric spike-field models (unified models) that can be used with existing decoding algorithms to reveal the timing of task or stimulus specific processing. Our proposed unified modeling framework captures the effects of two important features of information processing: time-varying stimulus-driven inputs and ongoing background activity that occurs even in the absence of environmental inputs. We have applied this framework for decoding neural latencies in simulated and experimentally recorded spike-field sessions obtained from the lateral intraparietal area (LIP) of awake, behaving monkeys performing cued look-and-reach movements to spatial targets. Using both simulated and experimental data, we find that estimates of trial-by-trial parameters are not significantly affected by the presence of ongoing background activity. However, including background activity in the unified model improves goodness of fit for predicting individual spiking events. Uncovering the relationship between the model parameters and the timing of movements offers new ways to test hypotheses about the relationship between neural activity and behavior. We obtained significant spike-field onset time correlations from single trials using a previously published data set where significantly strong correlation was only obtained through trial averaging. We also found that unified models extracted a stronger relationship between neural response latency and trial-by-trial behavioral performance than existing models of neural information processing. Our results highlight the utility of the unified modeling framework for characterizing spike-LFP recordings obtained during behavioral performance.
Neural Dynamics Underlying Event-Related Potentials

NASA Technical Reports Server (NTRS)

Shah, Ankoor S.; Bressler, Steven L.; Knuth, Kevin H.; Ding, Ming-Zhou; Mehta, Ashesh D.; Ulbert, Istvan; Schroeder, Charles E.

2003-01-01

There are two opposing hypotheses about the brain mechanisms underlying sensory event-related potentials (ERPs). One holds that sensory ERPs are generated by phase resetting of ongoing electroencephalographic (EEG) activity, and the other that they result from signal averaging of stimulus-evoked neural responses. We tested several contrasting predictions of these hypotheses by direct intracortical analysis of neural activity in monkeys. Our findings clearly demonstrate evoked response contributions to the sensory ERP in the monkey, and they suggest the likelihood that a mixed (Evoked/Phase Resetting) model may account for the generation of scalp ERPs in humans.
Milieu matters: Evidence that ongoing lifestyle activities influence health behaviors

PubMed Central

Lowe, Rob; Norman, Paul

2017-01-01

Health behaviors occur within a milieu of lifestyle activities that could conflict with health actions. We examined whether cognitions about, and performance of, other lifestyle activities augment the prediction of health behaviors, and whether these lifestyle factors are especially influential among individuals with low health behavior engagement. Participants (N = 211) completed measures of past behavior and cognitions relating to five health behaviors (e.g., smoking, getting drunk) and 23 lifestyle activities (e.g., reading, socializing), as well as personality variables. All behaviors were measured again at two weeks. Data were analyzed using neural network and cluster analyses. The neural network accurately predicted health behaviors at follow-up (R2 = .71). As hypothesized, lifestyle cognitions and activities independently predicted health behaviors over and above behavior-specific cognitions and previous behavior. Additionally, lifestyle activities and poor self-regulatory capability were more influential among people exhibiting unhealthy behaviors. Considering ongoing lifestyle activities can enhance prediction and understanding of health behaviors and offer new targets for health behavior interventions. PMID:28662120
Coherent ongoing subthreshold state of a cortical neural network regulated by slow- and fast-spiking interneurons.

PubMed

Hoshino, Osamu

2006-12-01

Although details of cortical interneurons in anatomy and physiology have been well understood, little is known about how they contribute to ongoing spontaneous neuronal activity that could have a great impact on subsequent neuronal information processing. Simulating a cortical neural network model of an early sensory area, we investigated whether and how two distinct types of inhibitory interneurons, or fast-spiking interneurons with narrow axonal arbors and slow-spiking interneurons with wide axonal arbors, have a spatiotemporal influence on the ongoing activity of principal cells and subsequent cognitive information processing. In the model, dynamic cell assemblies, or population activation of principal cells, expressed information about specific sensory features. Within cell assemblies, fast-spiking interneurons give a feedback inhibitory effect on principal cells. Between cell assemblies, slow-spiking interneurons give a lateral inhibitory effect on principal cells. Here, we show that these interneurons keep the network at a subthreshold level for action potential generation under the ongoing state, by which the reaction time of principal cells to sensory stimulation could be accelerated. We suggest that the best timing of inhibition mediated by fast-spiking interneurons and slow-spiking interneurons allows the network to remain near threshold for rapid responses to input.
Critical branching neural networks.

PubMed

Kello, Christopher T

2013-01-01

It is now well-established that intrinsic variations in human neural and behavioral activity tend to exhibit scaling laws in their fluctuations and distributions. The meaning of these scaling laws is an ongoing matter of debate between isolable causes versus pervasive causes. A spiking neural network model is presented that self-tunes to critical branching and, in doing so, simulates observed scaling laws as pervasive to neural and behavioral activity. These scaling laws are related to neural and cognitive functions, in that critical branching is shown to yield spiking activity with maximal memory and encoding capacities when analyzed using reservoir computing techniques. The model is also shown to account for findings of pervasive 1/f scaling in speech and cued response behaviors that are difficult to explain by isolable causes. Issues and questions raised by the model and its results are discussed from the perspectives of physics, neuroscience, computer and information sciences, and psychological and cognitive sciences.
A model of metastable dynamics during ongoing and evoked cortical activity

NASA Astrophysics Data System (ADS)

La Camera, Giancarlo

The dynamics of simultaneously recorded spike trains in alert animals often evolve through temporal sequences of metastable states. Little is known about the network mechanisms responsible for the genesis of such sequences, or their potential role in neural coding. In the gustatory cortex of alert rates, state sequences can be observed also in the absence of overt sensory stimulation, and thus form the basis of the so-called `ongoing activity'. This activity is characterized by a partial degree of coordination among neurons, sharp transitions among states, and multi-stability of single neurons' firing rates. A recurrent spiking network model with clustered topology can account for both the spontaneous generation of state sequences and the (network-generated) multi-stability. In the model, each network state results from the activation of specific neural clusters with potentiated intra-cluster connections. A mean field solution of the model shows a large number of stable states, each characterized by a subset of simultaneously active clusters. The firing rate in each cluster during ongoing activity depends on the number of active clusters, so that the same neuron can have different firing rates depending on the state of the network. Because of dense intra-cluster connectivity and recurrent inhibition, in finite networks the stable states lose stability due to finite size effects. Simulations of the dynamics show that the model ensemble activity continuously hops among the different states, reproducing the ongoing dynamics observed in the data. Moreover, when probed with external stimuli, the model correctly predicts the quenching of single neuron multi-stability into bi-stability, the reduction of dimensionality of the population activity, the reduction of trial-to-trial variability, and a potential role for metastable states in the anticipation of expected events. Altogether, these results provide a unified mechanistic model of ongoing and evoked cortical dynamics. NSF IIS-1161852, NIDCD K25-DC013557, NIDCD R01-DC010389.
Active Control of Complex Systems via Dynamic (Recurrent) Neural Networks

DTIC Science & Technology

1992-05-30

course, to on-going changes brought about by learning processes. As research in neurodynamics proceeded, the concept of reverberatory information flows...Microstructure of Cognition . Vol. 1: Foundations, M.I.T. Press, Cambridge, Massachusetts, pp. 354-361, 1986. 100 I Schwarz, G., "Estimating the dimension of a...Continually Running Fully Recurrent Neural Networks, ICS Report 8805, Institute of Cognitive Science, University of California at San Diego, 1988. 10 II
Motor Cortical Visuomotor Feedback Activity Is Initially Isolated from Downstream Targets in Output-Null Neural State Space Dimensions.

PubMed

Stavisky, Sergey D; Kao, Jonathan C; Ryu, Stephen I; Shenoy, Krishna V

2017-07-05

Neural circuits must transform new inputs into outputs without prematurely affecting downstream circuits while still maintaining other ongoing communication with these targets. We investigated how this isolation is achieved in the motor cortex when macaques received visual feedback signaling a movement perturbation. To overcome limitations in estimating the mapping from cortex to arm movements, we also conducted brain-machine interface (BMI) experiments where we could definitively identify neural firing patterns as output-null or output-potent. This revealed that perturbation-evoked responses were initially restricted to output-null patterns that cancelled out at the neural population code readout and only later entered output-potent neural dimensions. This mechanism was facilitated by the circuit's large null space and its ability to strongly modulate output-potent dimensions when generating corrective movements. These results show that the nervous system can temporarily isolate portions of a circuit's activity from its downstream targets by restricting this activity to the circuit's output-null neural dimensions. Copyright © 2017 Elsevier Inc. All rights reserved.
Prestimulus neural oscillations inhibit visual perception via modulation of response gain.

PubMed

Chaumon, Maximilien; Busch, Niko A

2014-11-01

The ongoing state of the brain radically affects how it processes sensory information. How does this ongoing brain activity interact with the processing of external stimuli? Spontaneous oscillations in the alpha range are thought to inhibit sensory processing, but little is known about the psychophysical mechanisms of this inhibition. We recorded ongoing brain activity with EEG while human observers performed a visual detection task with stimuli of different contrast intensities. To move beyond qualitative description, we formally compared psychometric functions obtained under different levels of ongoing alpha power and evaluated the inhibitory effect of ongoing alpha oscillations in terms of contrast or response gain models. This procedure opens the way to understanding the actual functional mechanisms by which ongoing brain activity affects visual performance. We found that strong prestimulus occipital alpha oscillations-but not more anterior mu oscillations-reduce performance most strongly for stimuli of the highest intensities tested. This inhibitory effect is best explained by a divisive reduction of response gain. Ongoing occipital alpha oscillations thus reflect changes in the visual system's input/output transformation that are independent of the sensory input to the system. They selectively scale the system's response, rather than change its sensitivity to sensory information.

Intrinsic and Extrinsic Neuromodulation of Olfactory Processing.

PubMed

Lizbinski, Kristyn M; Dacks, Andrew M

2017-01-01

Neuromodulation is a ubiquitous feature of neural systems, allowing flexible, context specific control over network dynamics. Neuromodulation was first described in invertebrate motor systems and early work established a basic dichotomy for neuromodulation as having either an intrinsic origin (i.e., neurons that participate in network coding) or an extrinsic origin (i.e., neurons from independent networks). In this conceptual dichotomy, intrinsic sources of neuromodulation provide a "memory" by adjusting network dynamics based upon previous and ongoing activation of the network itself, while extrinsic neuromodulators provide the context of ongoing activity of other neural networks. Although this dichotomy has been thoroughly considered in motor systems, it has received far less attention in sensory systems. In this review, we discuss intrinsic and extrinsic modulation in the context of olfactory processing in invertebrate and vertebrate model systems. We begin by discussing presynaptic modulation of olfactory sensory neurons by local interneurons (LNs) as a mechanism for gain control based on ongoing network activation. We then discuss the cell-class specific effects of serotonergic centrifugal neurons on olfactory processing. Finally, we briefly discuss the integration of intrinsic and extrinsic neuromodulation (metamodulation) as an effective mechanism for exerting global control over olfactory network dynamics. The heterogeneous nature of neuromodulation is a recurring theme throughout this review as the effects of both intrinsic and extrinsic modulation are generally non-uniform.
The Neural Bases of Difficult Speech Comprehension and Speech Production: Two Activation Likelihood Estimation (ALE) Meta-Analyses

ERIC Educational Resources Information Center

Adank, Patti

2012-01-01

The role of speech production mechanisms in difficult speech comprehension is the subject of on-going debate in speech science. Two Activation Likelihood Estimation (ALE) analyses were conducted on neuroimaging studies investigating difficult speech comprehension or speech production. Meta-analysis 1 included 10 studies contrasting comprehension…
Transcranial Alternating Current Stimulation (tACS) Mechanisms and Protocols

PubMed Central

Tavakoli, Amir V.; Yun, Kyongsik

2017-01-01

Perception, cognition and consciousness can be modulated as a function of oscillating neural activity, while ongoing neuronal dynamics are influenced by synaptic activity and membrane potential. Consequently, transcranial alternating current stimulation (tACS) may be used for neurological intervention. The advantageous features of tACS include the biphasic and sinusoidal tACS currents, the ability to entrain large neuronal populations, and subtle control over somatic effects. Through neuromodulation of phasic, neural activity, tACS is a powerful tool to investigate the neural correlates of cognition. The rapid development in this area requires clarity about best practices. Here we briefly introduce tACS and review the most compelling findings in the literature to provide a starting point for using tACS. We suggest that tACS protocols be based on functional brain mechanisms and appropriate control experiments, including active sham and condition blinding. PMID:28928634
Sex differences in the neural basis of emotional memories.

PubMed

Canli, Turhan; Desmond, John E; Zhao, Zuo; Gabrieli, John D E

2002-08-06

Psychological studies have found better memory in women than men for emotional events, but the neural basis for this difference is unknown. We used event-related functional MRI to assess whether sex differences in memory for emotional stimuli is associated with activation of different neural systems in men and women. Brain activation in 12 men and 12 women was recorded while they rated their experience of emotional arousal in response to neutral and emotionally negative pictures. In a recognition memory test 3 weeks after scanning, highly emotional pictures were remembered best, and remembered better by women than by men. Men and women activated different neural circuits to encode stimuli effectively into memory even when the analysis was restricted to pictures rated equally arousing by both groups. Men activated significantly more structures than women in a network that included the right amygdala, whereas women activated significantly fewer structures in a network that included the left amygdala. Women had significantly more brain regions where activation correlated with both ongoing evaluation of emotional experience and with subsequent memory for the most emotionally arousing pictures. Greater overlap in brain regions sensitive to current emotion and contributing to subsequent memory may be a neural mechanism for emotions to enhance memory more powerfully in women than in men.
Prenatal cocaine exposure, illicit-substance use and stress and craving processes during adolescence.

PubMed

Yip, Sarah W; Lacadie, Cheryl M; Sinha, Rajita; Mayes, Linda C; Potenza, Marc N

2016-01-01

Prenatal cocaine exposure (PCE) is associated with increased rates of illicit-substance use during adolescence. In addition, both PCE and illicit-substance use are associated with alterations in cortico-striato-limbic neurocircuitry, development of which is ongoing throughout adolescence. However, the relationship between illicit-substance use, PCE and functional neural responses has not previously been assessed concurrently. Sixty-eight adolescents were recruited from an ongoing longitudinal study of childhood and adolescent development. All participants had been followed since birth. Functional magnetic resonance imaging (fMRI) data were acquired during presentation of personalized stressful, favorite-food and neutral/relaxing imagery scripts and compared between 46 PCE and 22 non-prenatally-drug-exposed (NDE) adolescents with and without lifetime illicit-substance use initiation. Data were analyzed using multi-level ANOVAs (pFWE<.05). There was a significant three-way interaction between illicit-substance use, PCE status and cue condition on neural responses within primarily cortical brain regions, including regions of the left and right insula. Among PCE versus NDE adolescents, illicit-substance use was associated with decreased subcortical and increased cortical activity during the favorite-food condition, whereas the opposite pattern of activation was observed during the neutral/relaxing condition. Among PCE versus NDE adolescents, illicit-substance use during stress processing was associated with decreased activity in cortical and subcortical regions including amygdala, hippocampus and prefrontal cortex. Neural activity within cortico-striato-limbic regions was significantly negatively associated with subjective ratings of anxiety and craving among illicit-substance users, but not among non-users. These findings suggest different neural substrates of experimentation with illicit drugs between adolescents with and without in utero cocaine exposure. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Intrinsic and Extrinsic Neuromodulation of Olfactory Processing

PubMed Central

Lizbinski, Kristyn M.; Dacks, Andrew M.

2018-01-01

Neuromodulation is a ubiquitous feature of neural systems, allowing flexible, context specific control over network dynamics. Neuromodulation was first described in invertebrate motor systems and early work established a basic dichotomy for neuromodulation as having either an intrinsic origin (i.e., neurons that participate in network coding) or an extrinsic origin (i.e., neurons from independent networks). In this conceptual dichotomy, intrinsic sources of neuromodulation provide a “memory” by adjusting network dynamics based upon previous and ongoing activation of the network itself, while extrinsic neuromodulators provide the context of ongoing activity of other neural networks. Although this dichotomy has been thoroughly considered in motor systems, it has received far less attention in sensory systems. In this review, we discuss intrinsic and extrinsic modulation in the context of olfactory processing in invertebrate and vertebrate model systems. We begin by discussing presynaptic modulation of olfactory sensory neurons by local interneurons (LNs) as a mechanism for gain control based on ongoing network activation. We then discuss the cell-class specific effects of serotonergic centrifugal neurons on olfactory processing. Finally, we briefly discuss the integration of intrinsic and extrinsic neuromodulation (metamodulation) as an effective mechanism for exerting global control over olfactory network dynamics. The heterogeneous nature of neuromodulation is a recurring theme throughout this review as the effects of both intrinsic and extrinsic modulation are generally non-uniform. PMID:29375314
A Role of Phase-Resetting in Coordinating Large Scale Neural Networks During Attention and Goal-Directed Behavior

PubMed Central

Voloh, Benjamin; Womelsdorf, Thilo

2016-01-01

Short periods of oscillatory activation are ubiquitous signatures of neural circuits. A broad range of studies documents not only their circuit origins, but also a fundamental role for oscillatory activity in coordinating information transfer during goal directed behavior. Recent studies suggest that resetting the phase of ongoing oscillatory activity to endogenous or exogenous cues facilitates coordinated information transfer within circuits and between distributed brain areas. Here, we review evidence that pinpoints phase resetting as a critical marker of dynamic state changes of functional networks. Phase resets: (1) set a “neural context” in terms of narrow band frequencies that uniquely characterizes the activated circuits; (2) impose coherent low frequency phases to which high frequency activations can synchronize, identifiable as cross-frequency correlations across large anatomical distances; (3) are critical for neural coding models that depend on phase, increasing the informational content of neural representations; and (4) likely originate from the dynamics of canonical E-I circuits that are anatomically ubiquitous. These multiple signatures of phase resets are directly linked to enhanced information transfer and behavioral success. We survey how phase resets re-organize oscillations in diverse task contexts, including sensory perception, attentional stimulus selection, cross-modal integration, Pavlovian conditioning, and spatial navigation. The evidence we consider suggests that phase-resets can drive changes in neural excitability, ensemble organization, functional networks, and ultimately, overt behavior. PMID:27013986
How we perceive our own retina.

PubMed

Kirschfeld, Kuno

2017-10-25

Ever since the days of René Descartes, in the seventeenth century, the search for the relationship between subjective perception and neural activity has been an ongoing challenge. In neuroscience, an approach to the problem via the visual system has produced a paradigm using perceptual suppression, changing with time. Cortical areas in which the neural activity was modulated in temporal correlation with this percept could be traced. Although these areas may lead directly to perception, such temporal correlation of neural activity does not suffice as ultimate proof that they actually do so. In this article, I will use a different method to show that, for the perception of our own retina, any brain area leading directly to this perception also needs to represent the retina without distortion. Furthermore, I will demonstrate that the phenomenon of size constancy must be realized in this area. © 2017 The Authors.
Brain state-dependent recruitment of high-frequency oscillations in the human hippocampus.

PubMed

Billeke, Pablo; Ossandon, Tomas; Stockle, Marcelo; Perrone-Bertolotti, Marcela; Kahane, Philippe; Lachaux, Jean-Philippe; Fuentealba, Pablo

2017-09-01

Ripples are high-frequency bouts of coordinated hippocampal activity believed to be crucial for information transfer and memory formation. We used intracortical macroelectrodes to record neural activity in the human hippocampus of awake subjects undergoing surgical treatment for refractory epilepsy and distinguished two populations of ripple episodes based on their frequency spectrum. The phase-coupling of one population, slow ripples (90-110 Hz), to cortical delta oscillations was differentially modulated by cognitive task; whereas the second population, fast ripples (130-170 Hz), was not seemingly correlated to local neural activity. Furthermore, as cognitive tasks changed, the ongoing coordination of neural activity associated to slow ripples progressively augmented along the parahippocampal axis. Thus, during resting states, slow ripples were coordinated in restricted hippocampal territories; whereas during active states, such as attentionally-demanding tasks, high frequency activity emerged across the hippocampus and parahippocampal cortex, that was synchronized with slow ripples, consistent with ripples supporting information transfer and coupling anatomically distant regions. Hence, our results provide further evidence of neural diversity in hippocampal high-frequency oscillations and their association to cognitive processing in humans. Copyright © 2017 Elsevier Ltd. All rights reserved.
Neural Substrates of Spontaneous Musical Performance: An fMRI Study of Jazz Improvisation

PubMed Central

Limb, Charles J.; Braun, Allen R.

2008-01-01

To investigate the neural substrates that underlie spontaneous musical performance, we examined improvisation in professional jazz pianists using functional MRI. By employing two paradigms that differed widely in musical complexity, we found that improvisation (compared to production of over-learned musical sequences) was consistently characterized by a dissociated pattern of activity in the prefrontal cortex: extensive deactivation of dorsolateral prefrontal and lateral orbital regions with focal activation of the medial prefrontal (frontal polar) cortex. Such a pattern may reflect a combination of psychological processes required for spontaneous improvisation, in which internally motivated, stimulus-independent behaviors unfold in the absence of central processes that typically mediate self-monitoring and conscious volitional control of ongoing performance. Changes in prefrontal activity during improvisation were accompanied by widespread activation of neocortical sensorimotor areas (that mediate the organization and execution of musical performance) as well as deactivation of limbic structures (that regulate motivation and emotional tone). This distributed neural pattern may provide a cognitive context that enables the emergence of spontaneous creative activity. PMID:18301756
Neural substrates of spontaneous musical performance: an FMRI study of jazz improvisation.

PubMed

Limb, Charles J; Braun, Allen R

2008-02-27

To investigate the neural substrates that underlie spontaneous musical performance, we examined improvisation in professional jazz pianists using functional MRI. By employing two paradigms that differed widely in musical complexity, we found that improvisation (compared to production of over-learned musical sequences) was consistently characterized by a dissociated pattern of activity in the prefrontal cortex: extensive deactivation of dorsolateral prefrontal and lateral orbital regions with focal activation of the medial prefrontal (frontal polar) cortex. Such a pattern may reflect a combination of psychological processes required for spontaneous improvisation, in which internally motivated, stimulus-independent behaviors unfold in the absence of central processes that typically mediate self-monitoring and conscious volitional control of ongoing performance. Changes in prefrontal activity during improvisation were accompanied by widespread activation of neocortical sensorimotor areas (that mediate the organization and execution of musical performance) as well as deactivation of limbic structures (that regulate motivation and emotional tone). This distributed neural pattern may provide a cognitive context that enables the emergence of spontaneous creative activity.
Ongoing slow oscillatory phase modulates speech intelligibility in cooperation with motor cortical activity.

PubMed

Onojima, Takayuki; Kitajo, Keiichi; Mizuhara, Hiroaki

2017-01-01

Neural oscillation is attracting attention as an underlying mechanism for speech recognition. Speech intelligibility is enhanced by the synchronization of speech rhythms and slow neural oscillation, which is typically observed as human scalp electroencephalography (EEG). In addition to the effect of neural oscillation, it has been proposed that speech recognition is enhanced by the identification of a speaker's motor signals, which are used for speech production. To verify the relationship between the effect of neural oscillation and motor cortical activity, we measured scalp EEG, and simultaneous EEG and functional magnetic resonance imaging (fMRI) during a speech recognition task in which participants were required to recognize spoken words embedded in noise sound. We proposed an index to quantitatively evaluate the EEG phase effect on behavioral performance. The results showed that the delta and theta EEG phase before speech inputs modulated the participant's response time when conducting speech recognition tasks. The simultaneous EEG-fMRI experiment showed that slow EEG activity was correlated with motor cortical activity. These results suggested that the effect of the slow oscillatory phase was associated with the activity of the motor cortex during speech recognition.
Shades of grey; Assessing the contribution of the magno- and parvocellular systems to neural processing of the retinal input in the human visual system from the influence of neural population size and its discharge activity on the VEP.

PubMed

Marcar, Valentine L; Baselgia, Silvana; Lüthi-Eisenegger, Barbara; Jäncke, Lutz

2018-03-01

Retinal input processing in the human visual system involves a phasic and tonic neural response. We investigated the role of the magno- and parvocellular systems by comparing the influence of the active neural population size and its discharge activity on the amplitude and latency of four VEP components. We recorded the scalp electric potential of 20 human volunteers viewing a series of dartboard images presented as a pattern reversing and pattern on-/offset stimulus. These patterns were designed to vary both neural population size coding the temporal- and spatial luminance contrast property and the discharge activity of the population involved in a systematic manner. When the VEP amplitude reflected the size of the neural population coding the temporal luminance contrast property of the image, the influence of luminance contrast followed the contrast response function of the parvocellular system. When the VEP amplitude reflected the size of the neural population responding to the spatial luminance contrast property the image, the influence of luminance contrast followed the contrast response function of the magnocellular system. The latencies of the VEP components examined exhibited the same behavior across our stimulus series. This investigation demonstrates the complex interplay of the magno- and parvocellular systems on the neural response as captured by the VEP. It also demonstrates a linear relationship between stimulus property, neural response, and the VEP and reveals the importance of feedback projections in modulating the ongoing neural response. In doing so, it corroborates the conclusions of our previous study.
Local active information storage as a tool to understand distributed neural information processing

PubMed Central

Wibral, Michael; Lizier, Joseph T.; Vögler, Sebastian; Priesemann, Viola; Galuske, Ralf

2013-01-01

Every act of information processing can in principle be decomposed into the component operations of information storage, transfer, and modification. Yet, while this is easily done for today's digital computers, the application of these concepts to neural information processing was hampered by the lack of proper mathematical definitions of these operations on information. Recently, definitions were given for the dynamics of these information processing operations on a local scale in space and time in a distributed system, and the specific concept of local active information storage was successfully applied to the analysis and optimization of artificial neural systems. However, no attempt to measure the space-time dynamics of local active information storage in neural data has been made to date. Here we measure local active information storage on a local scale in time and space in voltage sensitive dye imaging data from area 18 of the cat. We show that storage reflects neural properties such as stimulus preferences and surprise upon unexpected stimulus change, and in area 18 reflects the abstract concept of an ongoing stimulus despite the locally random nature of this stimulus. We suggest that LAIS will be a useful quantity to test theories of cortical function, such as predictive coding. PMID:24501593
Attention and emotion: does rating emotion alter neural responses to amusing and sad films?

PubMed

Hutcherson, C A; Goldin, P R; Ochsner, K N; Gabrieli, J D; Barrett, L Feldman; Gross, J J

2005-09-01

Functional neuroimaging of affective systems often includes subjective self-report of the affective response. Although self-report provides valuable information regarding participants' affective responses, prior studies have raised the concern that the attentional demands of reporting on affective experience may obscure neural activations reflecting more natural affective responses. In the present study, we used potent emotion-eliciting amusing and sad films, employed a novel method of continuous self-reported rating of emotion experience, and compared the impact of rating with passive viewing of amusing and sad films. Subjective rating of ongoing emotional responses did not decrease either self-reported experience of emotion or neural activations relative to passive viewing in any brain regions. Rating, relative to passive viewing, produced increased activity in anterior cingulate, insula, and several other areas associated with introspection of emotion. These results support the use of continuous emotion measures and emotionally engaging films to study the dynamics of emotional responding and suggest that there may be some contexts in which the attention to emotion induced by reporting emotion experience does not disrupt emotional responding either behaviorally or neurally.
Augmenting distractor filtering via transcranial magnetic stimulation of the lateral occipital cortex.

PubMed

Eštočinová, Jana; Lo Gerfo, Emanuele; Della Libera, Chiara; Chelazzi, Leonardo; Santandrea, Elisa

2016-11-01

Visual selective attention (VSA) optimizes perception and behavioral control by enabling efficient selection of relevant information and filtering of distractors. While focusing resources on task-relevant information helps counteract distraction, dedicated filtering mechanisms have recently been demonstrated, allowing neural systems to implement suitable policies for the suppression of potential interference. Limited evidence is presently available concerning the neural underpinnings of these mechanisms, and whether neural circuitry within the visual cortex might play a causal role in their instantiation, a possibility that we directly tested here. In two related experiments, transcranial magnetic stimulation (TMS) was applied over the lateral occipital cortex of healthy humans at different times during the execution of a behavioral task which entailed varying levels of distractor interference and need for attentional engagement. While earlier TMS boosted target selection, stimulation within a restricted time epoch close to (and in the course of) stimulus presentation engendered selective enhancement of distractor suppression, by affecting the ongoing, reactive instantiation of attentional filtering mechanisms required by specific task conditions. The results attest to a causal role of mid-tier ventral visual areas in distractor filtering and offer insights into the mechanisms through which TMS may have affected ongoing neural activity in the stimulated tissue. Copyright © 2016 Elsevier Ltd. All rights reserved.
Decoding Ventromedial Hypothalamic Neural Activity during Male Mouse Aggression

PubMed Central

Dollar, Piotr; Perona, Pietro

2014-01-01

The ventromedial hypothalamus, ventrolateral area (VMHvl) was identified recently as a critical locus for inter-male aggression. Optogenetic stimulation of VMHvl in male mice evokes attack toward conspecifics and inactivation of the region inhibits natural aggression, yet very little is known about its underlying neural activity. To understand its role in promoting aggression, we recorded and analyzed neural activity in the VMHvl in response to a wide range of social and nonsocial stimuli. Although response profiles of VMHvl neurons are complex and heterogeneous, we identified a subpopulation of neurons that respond maximally during investigation and attack of male conspecific mice and during investigation of a source of male mouse urine. These “male responsive” neurons in the VMHvl are tuned to both the inter-male distance and the animal's velocity during attack. Additionally, VMHvl activity predicts several parameters of future aggressive action, including the latency and duration of the next attack. Linear regression analysis further demonstrates that aggression-specific parameters, such as distance, movement velocity, and attack latency, can model ongoing VMHvl activity fluctuation during inter-male encounters. These results represent the first effort to understand the hypothalamic neural activity during social behaviors using quantitative tools and suggest an important role for the VMHvl in encoding movement, sensory, and motivation-related signals. PMID:24760856
State-Dependent Decoding Algorithms Improve the Performance of a Bidirectional BMI in Anesthetized Rats.

PubMed

De Feo, Vito; Boi, Fabio; Safaai, Houman; Onken, Arno; Panzeri, Stefano; Vato, Alessandro

2017-01-01

Brain-machine interfaces (BMIs) promise to improve the quality of life of patients suffering from sensory and motor disabilities by creating a direct communication channel between the brain and the external world. Yet, their performance is currently limited by the relatively small amount of information that can be decoded from neural activity recorded form the brain. We have recently proposed that such decoding performance may be improved when using state-dependent decoding algorithms that predict and discount the large component of the trial-to-trial variability of neural activity which is due to the dependence of neural responses on the network's current internal state. Here we tested this idea by using a bidirectional BMI to investigate the gain in performance arising from using a state-dependent decoding algorithm. This BMI, implemented in anesthetized rats, controlled the movement of a dynamical system using neural activity decoded from motor cortex and fed back to the brain the dynamical system's position by electrically microstimulating somatosensory cortex. We found that using state-dependent algorithms that tracked the dynamics of ongoing activity led to an increase in the amount of information extracted form neural activity by 22%, with a consequently increase in all of the indices measuring the BMI's performance in controlling the dynamical system. This suggests that state-dependent decoding algorithms may be used to enhance BMIs at moderate computational cost.
NeuroGrid: recording action potentials from the surface of the brain.

PubMed

Khodagholy, Dion; Gelinas, Jennifer N; Thesen, Thomas; Doyle, Werner; Devinsky, Orrin; Malliaras, George G; Buzsáki, György

2015-02-01

Recording from neural networks at the resolution of action potentials is critical for understanding how information is processed in the brain. Here, we address this challenge by developing an organic material-based, ultraconformable, biocompatible and scalable neural interface array (the 'NeuroGrid') that can record both local field potentials(LFPs) and action potentials from superficial cortical neurons without penetrating the brain surface. Spikes with features of interneurons and pyramidal cells were simultaneously acquired by multiple neighboring electrodes of the NeuroGrid, allowing for the isolation of putative single neurons in rats. Spiking activity demonstrated consistent phase modulation by ongoing brain oscillations and was stable in recordings exceeding 1 week's duration. We also recorded LFP-modulated spiking activity intraoperatively in patients undergoing epilepsy surgery. The NeuroGrid constitutes an effective method for large-scale, stable recording of neuronal spikes in concert with local population synaptic activity, enhancing comprehension of neural processes across spatiotemporal scales and potentially facilitating diagnosis and therapy for brain disorders.
Age-Related Differences in the Temporal Dynamics of Prospective Memory Retrieval: A Lifespan Approach

ERIC Educational Resources Information Center

Mattli, Florentina; Zollig, Jacqueline; West, Robert

2011-01-01

The efficiency of prospective memory (PM) typically increases from childhood to young adulthood and then decreases in later adulthood. The current study used event-related brain potentials (ERPs) to examine the development of the neural correlates of processes associated with the detection of a PM cue, switching from the ongoing activity to the…

Correlated components of ongoing EEG point to emotionally laden attention - a possible marker of engagement?

PubMed

Dmochowski, Jacek P; Sajda, Paul; Dias, Joao; Parra, Lucas C

2012-01-01

Recent evidence from functional magnetic resonance imaging suggests that cortical hemodynamic responses coincide in different subjects experiencing a common naturalistic stimulus. Here we utilize neural responses in the electroencephalogram (EEG) evoked by multiple presentations of short film clips to index brain states marked by high levels of correlation within and across subjects. We formulate a novel signal decomposition method which extracts maximally correlated signal components from multiple EEG records. The resulting components capture correlations down to a one-second time resolution, thus revealing that peak correlations of neural activity across viewings can occur in remarkable correspondence with arousing moments of the film. Moreover, a significant reduction in neural correlation occurs upon a second viewing of the film or when the narrative is disrupted by presenting its scenes scrambled in time. We also probe oscillatory brain activity during periods of heightened correlation, and observe during such times a significant increase in the theta band for a frontal component and reductions in the alpha and beta frequency bands for parietal and occipital components. Low-resolution EEG tomography of these components suggests that the correlated neural activity is consistent with sources in the cingulate and orbitofrontal cortices. Put together, these results suggest that the observed synchrony reflects attention- and emotion-modulated cortical processing which may be decoded with high temporal resolution by extracting maximally correlated components of neural activity.
Correlated Components of Ongoing EEG Point to Emotionally Laden Attention – A Possible Marker of Engagement?

PubMed Central

Dmochowski, Jacek P.; Sajda, Paul; Dias, Joao; Parra, Lucas C.

2012-01-01

Recent evidence from functional magnetic resonance imaging suggests that cortical hemodynamic responses coincide in different subjects experiencing a common naturalistic stimulus. Here we utilize neural responses in the electroencephalogram (EEG) evoked by multiple presentations of short film clips to index brain states marked by high levels of correlation within and across subjects. We formulate a novel signal decomposition method which extracts maximally correlated signal components from multiple EEG records. The resulting components capture correlations down to a one-second time resolution, thus revealing that peak correlations of neural activity across viewings can occur in remarkable correspondence with arousing moments of the film. Moreover, a significant reduction in neural correlation occurs upon a second viewing of the film or when the narrative is disrupted by presenting its scenes scrambled in time. We also probe oscillatory brain activity during periods of heightened correlation, and observe during such times a significant increase in the theta band for a frontal component and reductions in the alpha and beta frequency bands for parietal and occipital components. Low-resolution EEG tomography of these components suggests that the correlated neural activity is consistent with sources in the cingulate and orbitofrontal cortices. Put together, these results suggest that the observed synchrony reflects attention- and emotion-modulated cortical processing which may be decoded with high temporal resolution by extracting maximally correlated components of neural activity. PMID:22623915
Operant conditioning of synaptic and spiking activity patterns in single hippocampal neurons.

PubMed

Ishikawa, Daisuke; Matsumoto, Nobuyoshi; Sakaguchi, Tetsuya; Matsuki, Norio; Ikegaya, Yuji

2014-04-02

Learning is a process of plastic adaptation through which a neural circuit generates a more preferable outcome; however, at a microscopic level, little is known about how synaptic activity is patterned into a desired configuration. Here, we report that animals can generate a specific form of synaptic activity in a given neuron in the hippocampus. In awake, head-restricted mice, we applied electrical stimulation to the lateral hypothalamus, a reward-associated brain region, when whole-cell patch-clamped CA1 neurons exhibited spontaneous synaptic activity that met preset criteria. Within 15 min, the mice learned to generate frequently the excitatory synaptic input pattern that satisfied the criteria. This reinforcement learning of synaptic activity was not observed for inhibitory input patterns. When a burst unit activity pattern was conditioned in paired and nonpaired paradigms, the frequency of burst-spiking events increased and decreased, respectively. The burst reinforcement occurred in the conditioned neuron but not in other adjacent neurons; however, ripple field oscillations were concomitantly reinforced. Neural conditioning depended on activation of NMDA receptors and dopamine D1 receptors. Acutely stressed mice and depression model mice that were subjected to forced swimming failed to exhibit the neural conditioning. This learning deficit was rescued by repetitive treatment with fluoxetine, an antidepressant. Therefore, internally motivated animals are capable of routing an ongoing action potential series into a specific neural pathway of the hippocampal network.
The neural correlates of reciprocity are sensitive to prior experience of reciprocity.

PubMed

Cáceda, Ricardo; Prendes-Alvarez, Stefania; Hsu, Jung-Jiin; Tripathi, Shanti P; Kilts, Clint D; James, G Andrew

2017-08-14

Reciprocity is central to human relationships and is strongly influenced by multiple factors including the nature of social exchanges and their attendant emotional reactions. Despite recent advances in the field, the neural processes involved in this modulation of reciprocal behavior by ongoing social interaction are poorly understood. We hypothesized that activity within a discrete set of neural networks including a putative moral cognitive neural network is associated with reciprocity behavior. Nineteen healthy adults underwent functional magnetic resonance imaging scanning while playing the trustee role in the Trust Game. Personality traits and moral development were assessed. Independent component analysis was used to identify task-related functional brain networks and assess their relationship to behavior. The saliency network (insula and anterior cingulate) was positively correlated with reciprocity behavior. A consistent array of brain regions supports the engagement of emotional, self-referential and planning processes during social reciprocity behavior. Published by Elsevier B.V.
Long-Term Memory Stabilized by Noise-Induced Rehearsal

PubMed Central

Wei, Yi

2014-01-01

Cortical networks can maintain memories for decades despite the short lifetime of synaptic strengths. Can a neural network store long-lasting memories in unstable synapses? Here, we study the effects of ongoing spike-timing-dependent plasticity (STDP) on the stability of memory patterns stored in synapses of an attractor neural network. We show that certain classes of STDP rules can stabilize all stored memory patterns despite a short lifetime of synapses. In our model, unstructured neural noise, after passing through the recurrent network connections, carries the imprint of all memory patterns in temporal correlations. STDP, combined with these correlations, leads to reinforcement of all stored patterns, even those that are never explicitly visited. Our findings may provide the functional reason for irregular spiking displayed by cortical neurons and justify models of system memory consolidation. Therefore, we propose that irregular neural activity is the feature that helps cortical networks maintain stable connections. PMID:25411507
Restoring Behavior via Inverse Neurocontroller in a Lesioned Cortical Spiking Model Driving a Virtual Arm

PubMed Central

Dura-Bernal, Salvador; Li, Kan; Neymotin, Samuel A.; Francis, Joseph T.; Principe, Jose C.; Lytton, William W.

2016-01-01

Neural stimulation can be used as a tool to elicit natural sensations or behaviors by modulating neural activity. This can be potentially used to mitigate the damage of brain lesions or neural disorders. However, in order to obtain the optimal stimulation sequences, it is necessary to develop neural control methods, for example by constructing an inverse model of the target system. For real brains, this can be very challenging, and often unfeasible, as it requires repeatedly stimulating the neural system to obtain enough probing data, and depends on an unwarranted assumption of stationarity. By contrast, detailed brain simulations may provide an alternative testbed for understanding the interactions between ongoing neural activity and external stimulation. Unlike real brains, the artificial system can be probed extensively and precisely, and detailed output information is readily available. Here we employed a spiking network model of sensorimotor cortex trained to drive a realistic virtual musculoskeletal arm to reach a target. The network was then perturbed, in order to simulate a lesion, by either silencing neurons or removing synaptic connections. All lesions led to significant behvaioral impairments during the reaching task. The remaining cells were then systematically probed with a set of single and multiple-cell stimulations, and results were used to build an inverse model of the neural system. The inverse model was constructed using a kernel adaptive filtering method, and was used to predict the neural stimulation pattern required to recover the pre-lesion neural activity. Applying the derived neurostimulation to the lesioned network improved the reaching behavior performance. This work proposes a novel neurocontrol method, and provides theoretical groundwork on the use biomimetic brain models to develop and evaluate neurocontrollers that restore the function of damaged brain regions and the corresponding motor behaviors. PMID:26903796
Auditory Magnetoencephalographic Frequency-Tagged Responses Mirror the Ongoing Segmentation Processes Underlying Statistical Learning.

PubMed

Farthouat, Juliane; Franco, Ana; Mary, Alison; Delpouve, Julie; Wens, Vincent; Op de Beeck, Marc; De Tiège, Xavier; Peigneux, Philippe

2017-03-01

Humans are highly sensitive to statistical regularities in their environment. This phenomenon, usually referred as statistical learning, is most often assessed using post-learning behavioural measures that are limited by a lack of sensibility and do not monitor the temporal dynamics of learning. In the present study, we used magnetoencephalographic frequency-tagged responses to investigate the neural sources and temporal development of the ongoing brain activity that supports the detection of regularities embedded in auditory streams. Participants passively listened to statistical streams in which tones were grouped as triplets, and to random streams in which tones were randomly presented. Results show that during exposure to statistical (vs. random) streams, tritone frequency-related responses reflecting the learning of regularities embedded in the stream increased in the left supplementary motor area and left posterior superior temporal sulcus (pSTS), whereas tone frequency-related responses decreased in the right angular gyrus and right pSTS. Tritone frequency-related responses rapidly developed to reach significance after 3 min of exposure. These results suggest that the incidental extraction of novel regularities is subtended by a gradual shift from rhythmic activity reflecting individual tone succession toward rhythmic activity synchronised with triplet presentation, and that these rhythmic processes are subtended by distinct neural sources.
Periodicity of high-order neural functions

NASA Technical Reports Server (NTRS)

Kellaway, P.; Borda, R. P.; Frost, J. D.; Carrie, J. R. G.; Coats, A. C.

1973-01-01

The results of recent studies on higher order, integrative processes in the central nervous system are reported. Attempts were made to determine whether these processes exhibit any ongoing rhythmicity which might manifest itself in alterations of attention and alertness. Experiments were also designed to determine if a periodicity approximating that of the REM could be detected in various parameters of brain electrical activity.
Neural Repetition Effects in the Medial Temporal Lobe Complex are Modulated by Previous Encoding Experience

PubMed Central

Greene, Ciara M.; Soto, David

2012-01-01

It remains an intriguing question why the medial temporal lobe (MTL) can display either attenuation or enhancement of neural activity following repetition of previously studied items. To isolate the role of encoding experience itself, we assessed neural repetition effects in the absence of any ongoing task demand or intentional orientation to retrieve. Experiment 1 showed that the hippocampus and surrounding MTL regions displayed neural repetition suppression (RS) upon repetition of past items that were merely attended during an earlier study phase but this was not the case following re-occurrence of items that had been encoded into working memory (WM). In this latter case a trend toward neural repetition enhancement (RE) was observed, though this was highly variable across individuals. Interestingly, participants with a higher degree of neural RE in the MTL complex displayed higher memory sensitivity in a later, surprise recognition test. Experiment 2 showed that massive exposure at encoding effected a change in the neural architecture supporting incidental repetition effects, with regions of the posterior parietal and ventral-frontal cortex in addition to the hippocampus displaying neural RE, while no neural RS was observed. The nature of encoding experience therefore modulates the expression of neural repetition effects in the MTL and the neocortex in the absence of memory goals. PMID:22829892
Drug Delivery to the Inner Ear

PubMed Central

Wise, Andrew K; Gillespie, Lisa N

2012-01-01

Bionic devices electrically activate neural populations to partially restore lost function. Of fundamental importance is the functional integrity of the targeted neurons. However, in many conditions the ongoing pathology can lead to continued neural degeneration and death that may compromise the effectiveness of the device and limit future strategies to improve performance. The use of drugs that can prevent nerve cell degeneration and promote their regeneration may improve clinical outcomes. In this paper we focus on strategies of delivering neuroprotective drugs to the auditory system in a way that is safe and clinically relevant for use in combination with a cochlear implant. The aim of this approach is to prevent neural degeneration and promote nerve regrowth in order to improve outcomes for cochlear implant recipients using techniques that can be translated to the clinic. PMID:23186937
Rhythmic neural activity indicates the contribution of attention and memory to the processing of occluded movements in 10-month-old infants.

PubMed

Bache, Cathleen; Kopp, Franziska; Springer, Anne; Stadler, Waltraud; Lindenberger, Ulman; Werkle-Bergner, Markus

2015-11-01

Infants possess the remarkable capacity to perceive occluded movements as ongoing and coherent. Little is known about the neural mechanisms that enable internal representation of conspecifics' and inanimate objects' movements during visual occlusion. In this study, 10-month-old infants watched briefly occluded human and object movements. Prior to occlusion, continuous and distorted versions of the movement were shown. EEG recordings were used to assess neural activity assumed to relate to processes of attention (occipital alpha), memory (frontal theta), and sensorimotor simulation (central alpha) before, during, and after occlusion. Oscillatory activity was analyzed using an individualized data approach taking idiosyncrasies into account. Results for occipital alpha were consistent with infants' preference for attending to social stimuli. Furthermore, frontal theta activity was more pronounced when tracking distorted as opposed to continuous movement, and when maintaining object as opposed to human movement. Central alpha did not discriminate between experimental conditions. In sum, we conclude that observing occluded movements recruits processes of attention and memory which are modulated by stimulus and movement properties. Copyright © 2015 Elsevier B.V. All rights reserved.
Alteration of neural action potential patterns by axonal stimulation: the importance of stimulus location.

PubMed

Crago, Patrick E; Makowski, Nathaniel S

2014-10-01

Stimulation of peripheral nerves is often superimposed on ongoing motor and sensory activity in the same axons, without a quantitative model of the net action potential train at the axon endpoint. We develop a model of action potential patterns elicited by superimposing constant frequency axonal stimulation on the action potentials arriving from a physiologically activated neural source. The model includes interactions due to collision block, resetting of the neural impulse generator, and the refractory period of the axon at the point of stimulation. Both the mean endpoint firing rate and the probability distribution of the action potential firing periods depend strongly on the relative firing rates of the two sources and the intersite conduction time between them. When the stimulus rate exceeds the neural rate, neural action potentials do not reach the endpoint and the rate of endpoint action potentials is the same as the stimulus rate, regardless of the intersite conduction time. However, when the stimulus rate is less than the neural rate, and the intersite conduction time is short, the two rates partially sum. Increases in stimulus rate produce non-monotonic increases in endpoint rate and continuously increasing block of neurally generated action potentials. Rate summation is reduced and more neural action potentials are blocked as the intersite conduction time increases. At long intersite conduction times, the endpoint rate simplifies to being the maximum of either the neural or the stimulus rate. This study highlights the potential of increasing the endpoint action potential rate and preserving neural information transmission by low rate stimulation with short intersite conduction times. Intersite conduction times can be decreased with proximal stimulation sites for muscles and distal stimulation sites for sensory endings. The model provides a basis for optimizing experiments and designing neuroprosthetic interventions involving motor or sensory stimulation.
Midfrontal conflict-related theta-band power reflects neural oscillations that predict behavior.

PubMed

Cohen, Michael X; Donner, Tobias H

2013-12-01

Action monitoring and conflict resolution require the rapid and flexible coordination of activity in multiple brain regions. Oscillatory neural population activity may be a key physiological mechanism underlying such rapid and flexible network coordination. EEG power modulations of theta-band (4-8 Hz) activity over the human midfrontal cortex during response conflict have been proposed to reflect neural oscillations that support conflict detection and resolution processes. However, it has remained unclear whether this frequency-band-specific activity reflects neural oscillations or nonoscillatory responses (i.e., event-related potentials). Here, we show that removing the phase-locked component of the EEG did not reduce the strength of the conflict-related modulation of the residual (i.e., non-phase-locked) theta power over midfrontal cortex. Furthermore, within-subject regression analyses revealed that the non-phase-locked theta power was a significantly better predictor of the conflict condition than was the time-domain phase-locked EEG component. Finally, non-phase-locked theta power showed robust and condition-specific (high- vs. low-conflict) cross-trial correlations with reaction time, whereas the phase-locked component did not. Taken together, our results indicate that most of the conflict-related and behaviorally relevant midfrontal EEG signal reflects a modulation of ongoing theta-band oscillations that occurs during the decision process but is not phase-locked to the stimulus or to the response.
Investigating habits: strategies, technologies and models

PubMed Central

Smith, Kyle S.; Graybiel, Ann M.

2014-01-01

Understanding habits at a biological level requires a combination of behavioral observations and measures of ongoing neural activity. Theoretical frameworks as well as definitions of habitual behaviors emerging from classic behavioral research have been enriched by new approaches taking account of the identification of brain regions and circuits related to habitual behavior. Together, this combination of experimental and theoretical work has provided key insights into how brain circuits underlying action-learning and action-selection are organized, and how a balance between behavioral flexibility and fixity is achieved. New methods to monitor and manipulate neural activity in real time are allowing us to have a first look “under the hood” of a habit as it is formed and expressed. Here we discuss ideas emerging from such approaches. We pay special attention to the unexpected findings that have arisen from our own experiments suggesting that habitual behaviors likely require the simultaneous activity of multiple distinct components, or operators, seen as responsible for the contrasting dynamics of neural activity in both cortico-limbic and sensorimotor circuits recorded concurrently during different stages of habit learning. The neural dynamics identified thus far do not fully meet expectations derived from traditional models of the structure of habits, and the behavioral measures of habits that we have made also are not fully aligned with these models. We explore these new clues as opportunities to refine an understanding of habits. PMID:24574988
Detection of deception based on fMRI activation patterns underlying the production of a deceptive response and receiving feedback about the success of the deception after a mock murder crime

PubMed Central

Cui, Qian; Vanman, Eric J.; Wei, Dongtao; Yang, Wenjing; Jia, Lei

2014-01-01

The ability of a deceiver to track a victim’s ongoing judgments about the truthfulness of the deceit can be critical for successful deception. However, no study has yet investigated the neural circuits underlying receiving a judgment about one’s lie. To explore this issue, we used a modified Guilty Knowledge Test in a mock murder situation to simultaneously record the neural responses involved in producing deception and later when judgments of that deception were made. Producing deception recruited the bilateral inferior parietal lobules (IPLs), right ventral lateral prefrontal (VLPF) areas and right striatum, among which the activation of the right VLPF contributed mostly to diagnosing the identities of the participants, correctly diagnosing 81.25% of ‘murderers’ and 81.25% of ‘innocents’. Moreover, the participant’s response when their deception was successful uniquely recruited the right middle frontal gyrus, bilateral IPLs, bilateral orbitofrontal cortices, bilateral middle temporal gyrus and left cerebellum, among which the right IPL contributed mostly to diagnosing participants’ identities, correctly diagnosing 93.75% of murderers and 87.5% of innocents. This study shows that neural activity associated with being a successful liar (or not) is a feasible indicator for detecting lies and may be more valid than neural activity associated with producing deception. PMID:23946002
Neural Reward Processing Mediates the Relationship between Insomnia Symptoms and Depression in Adolescence

PubMed Central

Casement, Melynda D.; Keenan, Kate E.; Hipwell, Alison E.; Guyer, Amanda E.; Forbes, Erika E.

2016-01-01

Study Objectives: Emerging evidence suggests that insomnia may disrupt reward-related brain function—a potentially important factor in the development of depressive disorder. Adolescence may be a period during which such disruption is especially problematic given the rise in the incidence of insomnia and ongoing development of neural systems that support reward processing. The present study uses longitudinal data to test the hypothesis that disruption of neural reward processing is a mechanism by which insomnia symptoms—including nocturnal insomnia symptoms (NIS) and nonrestorative sleep (NRS)—contribute to depressive symptoms in adolescent girls. Method: Participants were 123 adolescent girls and their caregivers from an ongoing longitudinal study of precursors to depression across adolescent development. NIS and NRS were assessed annually from ages 9 to 13 years. Girls completed a monetary reward task during a functional MRI scan at age 16 years. Depressive symptoms were assessed at ages 16 and 17 years. Multivariable regression tested the prospective associations between NIS and NRS, neural response during reward anticipation, and the mean number of depressive symptoms (omitting sleep problems). Results: NRS, but not NIS, during early adolescence was positively associated with late adolescent dorsal medial prefrontal cortex (dmPFC) response to reward anticipation and depressive symptoms. DMPFC response mediated the relationship between early adolescent NRS and late adolescent depressive symptoms. Conclusions: These results suggest that NRS may contribute to depression by disrupting reward processing via altered activity in a region of prefrontal cortex involved in affective control. The results also support the mechanistic differentiation of NIS and NRS. Citation: Casement MD, Keenan KE, Hipwell AE, Guyer AE, Forbes EE. Neural reward processing mediates the relationship between insomnia symptoms and depression in adolescence. SLEEP 2016;39(2):439–447. PMID:26350468
Dynamic effective connectivity in cortically embedded systems of recurrently coupled synfire chains.

PubMed

Trengove, Chris; Diesmann, Markus; van Leeuwen, Cees

2016-02-01

As a candidate mechanism of neural representation, large numbers of synfire chains can efficiently be embedded in a balanced recurrent cortical network model. Here we study a model in which multiple synfire chains of variable strength are randomly coupled together to form a recurrent system. The system can be implemented both as a large-scale network of integrate-and-fire neurons and as a reduced model. The latter has binary-state pools as basic units but is otherwise isomorphic to the large-scale model, and provides an efficient tool for studying its behavior. Both the large-scale system and its reduced counterpart are able to sustain ongoing endogenous activity in the form of synfire waves, the proliferation of which is regulated by negative feedback caused by collateral noise. Within this equilibrium, diverse repertoires of ongoing activity are observed, including meta-stability and multiple steady states. These states arise in concert with an effective connectivity structure (ECS). The ECS admits a family of effective connectivity graphs (ECGs), parametrized by the mean global activity level. Of these graphs, the strongly connected components and their associated out-components account to a large extent for the observed steady states of the system. These results imply a notion of dynamic effective connectivity as governing neural computation with synfire chains, and related forms of cortical circuitry with complex topologies.
A theory of how active behavior stabilises neural activity: Neural gain modulation by closed-loop environmental feedback

PubMed Central

2018-01-01

During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence of neural fluctuations, across the brain, on closed-loop brain/body/environment interactions strongly supporting the idea that brain function cannot be fully understood through open-loop approaches alone. PMID:29342146
A theory of how active behavior stabilises neural activity: Neural gain modulation by closed-loop environmental feedback.

PubMed

Buckley, Christopher L; Toyoizumi, Taro

2018-01-01

During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence of neural fluctuations, across the brain, on closed-loop brain/body/environment interactions strongly supporting the idea that brain function cannot be fully understood through open-loop approaches alone.
Animal-to-Animal Variation in Odor Preference and Neural Representation of Odors

NASA Astrophysics Data System (ADS)

Honegger, Kyle; Smith, Matthew; Turner, Glenn; de Bivort, Benjamin

Across any population of animals, individuals exhibit diverse behaviors and reactions to sensory stimuli like tastes and odors. While idiosyncratic behavior is ubiquitous, its biological basis is poorly understood. In this talk, I will present evidence that individual fruit flies (Drosophila melanogaster) display idiosyncratic olfactory behaviors and discuss our ongoing efforts to map these behavioral differences to variation in neural circuits. Using a high-throughput, single-fly assay for odor preference, we have demonstrated that highly inbred flies display substantial animal-to-animal variability, beyond that expected from experimental error, and that these preferences persist over days. Using in vivo two-photon calcium imaging, we are beginning to examine the idiosyncrasy of neural coding in the fly olfactory pathway and find that the odor responses of individual processing channels in the antennal lobe can vary substantially from fly to fly. These results imply that individual differences in neural coding may be used to predict the idiosyncratic behavior of an individual - a hypothesis we are currently testing by imaging neural activity from flies after measuring their odor preferences.

Long-term memory stabilized by noise-induced rehearsal.

PubMed

Wei, Yi; Koulakov, Alexei A

2014-11-19

Cortical networks can maintain memories for decades despite the short lifetime of synaptic strengths. Can a neural network store long-lasting memories in unstable synapses? Here, we study the effects of ongoing spike-timing-dependent plasticity (STDP) on the stability of memory patterns stored in synapses of an attractor neural network. We show that certain classes of STDP rules can stabilize all stored memory patterns despite a short lifetime of synapses. In our model, unstructured neural noise, after passing through the recurrent network connections, carries the imprint of all memory patterns in temporal correlations. STDP, combined with these correlations, leads to reinforcement of all stored patterns, even those that are never explicitly visited. Our findings may provide the functional reason for irregular spiking displayed by cortical neurons and justify models of system memory consolidation. Therefore, we propose that irregular neural activity is the feature that helps cortical networks maintain stable connections. Copyright © 2014 the authors 0270-6474/14/3415804-12$15.00/0.
The Brain in its Body: Motor Control and Sensing in a Biomechanical Context

PubMed Central

Chiel, Hillel J.; Ting, Lena H.; Ekeberg, Orjan; Hartmann, Mitra J. Z.

2009-01-01

Although it is widely recognized that adaptive behavior emerges from the ongoing interactions among the nervous system, the body, and the environment, it has only become possible in recent years to experimentally study and to simulate these interacting systems. We briefly review work on molluscan feeding, maintenance of postural control in cats and humans, simulations of locomotion in lamprey, insect, cat and salamander, and active vibrissal sensing in rats to illustrate the insights that can be derived from studies of neural control and sensing within a biomechanical context. These studies illustrate that control may be shared between the nervous system and the periphery, that neural activity organizes degrees of freedom into biomechanically meaningful subsets, that mechanics alone may play crucial roles in enforcing gait patterns, and that mechanics of sensors is crucial for their function. PMID:19828793
Noradrenergic Regulation of Central Amygdala in Aversive Pavlovian-to-Instrumental Transfer

PubMed Central

Soroeta, Jose M.

2017-01-01

Abstract The neural mechanisms through which a Pavlovian conditioned stimulus (CS) elicits innate defense responses are well understood. But a Pavlovian CS can also invigorate ongoing instrumental responding, as shown by studies of aversive Pavlovian-to-instrumental transfer (PIT). While the neural circuitry of appetitive PIT has been studied extensively, little is known about the brain mechanisms of aversive PIT. We recently showed the central amygdala (CeA) is essential for aversive PIT. In the current studies, using pharmacology and designer receptors in rodents, we demonstrate that noradrenergic (NE) activity negatively regulates PIT via brainstem locus coeruleus (LC) activity and LC projections to CeA. Our results provide evidence for a novel pathway through which response modulation occurs between brainstem neuromodulatory systems and CeA to invigorate adaptive behavior in the face of threat. PMID:29071299
Manipulating motor performance and memory through real-time fMRI neurofeedback.

PubMed

Scharnowski, Frank; Veit, Ralf; Zopf, Regine; Studer, Petra; Bock, Simon; Diedrichsen, Jörn; Goebel, Rainer; Mathiak, Klaus; Birbaumer, Niels; Weiskopf, Nikolaus

2015-05-01

Task performance depends on ongoing brain activity which can be influenced by attention, arousal, or motivation. However, such modulating factors of cognitive efficiency are unspecific, can be difficult to control, and are not suitable to facilitate neural processing in a regionally specific manner. Here, we non-pharmacologically manipulated regionally specific brain activity using technically sophisticated real-time fMRI neurofeedback. This was accomplished by training participants to simultaneously control ongoing brain activity in circumscribed motor and memory-related brain areas, namely the supplementary motor area and the parahippocampal cortex. We found that learned voluntary control over these functionally distinct brain areas caused functionally specific behavioral effects, i.e. shortening of motor reaction times and specific interference with memory encoding. The neurofeedback approach goes beyond improving cognitive efficiency by unspecific psychological factors such as attention, arousal, or motivation. It allows for directly manipulating sustained activity of task-relevant brain regions in order to yield specific behavioral or cognitive effects. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.
Manipulating motor performance and memory through real-time fMRI neurofeedback

PubMed Central

Scharnowski, Frank; Veit, Ralf; Zopf, Regine; Studer, Petra; Bock, Simon; Diedrichsen, Jörn; Goebel, Rainer; Mathiak, Klaus; Birbaumer, Niels; Weiskopf, Nikolaus

2015-01-01

Task performance depends on ongoing brain activity which can be influenced by attention, arousal, or motivation. However, such modulating factors of cognitive efficiency are unspecific, can be difficult to control, and are not suitable to facilitate neural processing in a regionally specific manner. Here, we non-pharmacologically manipulated regionally specific brain activity using technically sophisticated real-time fMRI neurofeedback. This was accomplished by training participants to simultaneously control ongoing brain activity in circumscribed motor and memory-related brain areas, namely the supplementary motor area and the parahippocampal cortex. We found that learned voluntary control over these functionally distinct brain areas caused functionally specific behavioral effects, i.e. shortening of motor reaction times and specific interference with memory encoding. The neurofeedback approach goes beyond improving cognitive efficiency by unspecific psychological factors such as attention, arousal, or motivation. It allows for directly manipulating sustained activity of task-relevant brain regions in order to yield specific behavioral or cognitive effects. PMID:25796342
Ongoing behavior predicts perceptual report of interval duration

PubMed Central

Gouvêa, Thiago S.; Monteiro, Tiago; Soares, Sofia; Atallah, Bassam V.; Paton, Joseph J.

2014-01-01

The ability to estimate the passage of time is essential for adaptive behavior in complex environments. Yet, it is not known how the brain encodes time over the durations necessary to explain animal behavior. Under temporally structured reinforcement schedules, animals tend to develop temporally structured behavior, and interval timing has been suggested to be accomplished by learning sequences of behavioral states. If this is true, trial to trial fluctuations in behavioral sequences should be predictive of fluctuations in time estimation. We trained rodents in an duration categorization task while continuously monitoring their behavior with a high speed camera. Animals developed highly reproducible behavioral sequences during the interval being timed. Moreover, those sequences were often predictive of perceptual report from early in the trial, providing support to the idea that animals may use learned behavioral patterns to estimate the duration of time intervals. To better resolve the issue, we propose that continuous and simultaneous behavioral and neural monitoring will enable identification of neural activity related to time perception that is not explained by ongoing behavior. PMID:24672473
Differential coding of reward and movement information in the dorsomedial striatal direct and indirect pathways.

PubMed

Shin, Jung Hwan; Kim, Dohoung; Jung, Min Whan

2018-01-26

The direct and indirect pathways of the basal ganglia have long been thought to mediate behavioral promotion and inhibition, respectively. However, this classic dichotomous model has been recently challenged. To better understand neural processes underlying reward-based learning and movement control, we recorded from direct (dSPNs) and indirect (iSPNs) pathway spiny projection neurons in the dorsomedial striatum of D1-Cre and D2-Cre mice performing a probabilistic Pavlovian conditioning task. dSPNs tend to increase activity while iSPNs decrease activity as a function of reward value, suggesting the striatum represents value in the relative activity levels of dSPNs versus iSPNs. Lick offset-related activity increase is largely dSPN selective, suggesting dSPN involvement in suppressing ongoing licking behavior. Rapid responses to negative outcome and previous reward-related responses are more frequent among iSPNs than dSPNs, suggesting stronger contributions of iSPNs to outcome-dependent behavioral adjustment. These findings provide new insights into striatal neural circuit operations.
Neural Reward Processing Mediates the Relationship between Insomnia Symptoms and Depression in Adolescence.

PubMed

Casement, Melynda D; Keenan, Kate E; Hipwell, Alison E; Guyer, Amanda E; Forbes, Erika E

2016-02-01

Emerging evidence suggests that insomnia may disrupt reward-related brain function-a potentially important factor in the development of depressive disorder. Adolescence may be a period during which such disruption is especially problematic given the rise in the incidence of insomnia and ongoing development of neural systems that support reward processing. The present study uses longitudinal data to test the hypothesis that disruption of neural reward processing is a mechanism by which insomnia symptoms-including nocturnal insomnia symptoms (NIS) and nonrestorative sleep (NRS)-contribute to depressive symptoms in adolescent girls. Participants were 123 adolescent girls and their caregivers from an ongoing longitudinal study of precursors to depression across adolescent development. NIS and NRS were assessed annually from ages 9 to 13 years. Girls completed a monetary reward task during a functional MRI scan at age 16 years. Depressive symptoms were assessed at ages 16 and 17 years. Multivariable regression tested the prospective associations between NIS and NRS, neural response during reward anticipation, and the mean number of depressive symptoms (omitting sleep problems). NRS, but not NIS, during early adolescence was positively associated with late adolescent dorsal medial prefrontal cortex (dmPFC) response to reward anticipation and depressive symptoms. DMPFC response mediated the relationship between early adolescent NRS and late adolescent depressive symptoms. These results suggest that NRS may contribute to depression by disrupting reward processing via altered activity in a region of prefrontal cortex involved in affective control. The results also support the mechanistic differentiation of NIS and NRS. © 2016 Associated Professional Sleep Societies, LLC.
Differential effects of ongoing EEG beta and theta power on memory formation

PubMed Central

Scholz, Sebastian; Schneider, Signe Luisa

2017-01-01

Recently, elevated ongoing pre-stimulus beta power (13–17 Hz) at encoding has been associated with subsequent memory formation for visual stimulus material. It is unclear whether this activity is merely specific to visual processing or whether it reflects a state facilitating general memory formation, independent of stimulus modality. To answer that question, the present study investigated the relationship between neural pre-stimulus oscillations and verbal memory formation in different sensory modalities. For that purpose, a within-subject design was employed to explore differences between successful and failed memory formation in the visual and auditory modality. Furthermore, associative memory was addressed by presenting the stimuli in combination with background images. Results revealed that similar EEG activity in the low beta frequency range (13–17 Hz) is associated with subsequent memory success, independent of stimulus modality. Elevated power prior to stimulus onset differentiated successful from failed memory formation. In contrast, differential effects between modalities were found in the theta band (3–7 Hz), with an increased oscillatory activity before the onset of later remembered visually presented words. In addition, pre-stimulus theta power dissociated between successful and failed encoding of associated context, independent of the stimulus modality of the item itself. We therefore suggest that increased ongoing low beta activity reflects a memory promoting state, which is likely to be moderated by modality-independent attentional or inhibitory processes, whereas high ongoing theta power is suggested as an indicator of the enhanced binding of incoming interlinked information. PMID:28192459
Interfacing to the brain’s motor decisions

PubMed Central

2017-01-01

It has been long known that neural activity, recorded with electrophysiological methods, contains rich information about a subject’s motor intentions, sensory experiences, allocation of attention, action planning, and even abstract thoughts. All these functions have been the subject of neurophysiological investigations, with the goal of understanding how neuronal activity represents behavioral parameters, sensory inputs, and cognitive functions. The field of brain-machine interfaces (BMIs) strives for a somewhat different goal: it endeavors to extract information from neural modulations to create a communication link between the brain and external devices. Although many remarkable successes have been already achieved in the BMI field, questions remain regarding the possibility of decoding high-order neural representations, such as decision making. Could BMIs be employed to decode the neural representations of decisions underlying goal-directed actions? In this review we lay out a framework that describes the computations underlying goal-directed actions as a multistep process performed by multiple cortical and subcortical areas. We then discuss how BMIs could connect to different decision-making steps and decode the neural processing ongoing before movements are initiated. Such decision-making BMIs could operate as a system with prediction that offers many advantages, such as shorter reaction time, better error processing, and improved unsupervised learning. To present the current state of the art, we review several recent BMIs incorporating decision-making components. PMID:28003406
A Neural Model for Language and Speech.

ERIC Educational Resources Information Center

Buckingham, Hugh W., Jr.; Hollien, Harry

1978-01-01

A neural model in the form of a servo-mechanism is developed to account for certain aspects of language and speech in the human nervous system. Emphasis is placed on encoding processes as well as on-going feedback during production. (SW)
Differential modulation of auditory responses to attended and unattended speech in different listening conditions

PubMed Central

Kong, Ying-Yee; Mullangi, Ala; Ding, Nai

2014-01-01

This study investigates how top-down attention modulates neural tracking of the speech envelope in different listening conditions. In the quiet conditions, a single speech stream was presented and the subjects paid attention to the speech stream (active listening) or watched a silent movie instead (passive listening). In the competing speaker (CS) conditions, two speakers of opposite genders were presented diotically. Ongoing electroencephalographic (EEG) responses were measured in each condition and cross-correlated with the speech envelope of each speaker at different time lags. In quiet, active and passive listening resulted in similar neural responses to the speech envelope. In the CS conditions, however, the shape of the cross-correlation function was remarkably different between the attended and unattended speech. The cross-correlation with the attended speech showed stronger N1 and P2 responses but a weaker P1 response compared with the cross-correlation with the unattended speech. Furthermore, the N1 response to the attended speech in the CS condition was enhanced and delayed compared with the active listening condition in quiet, while the P2 response to the unattended speaker in the CS condition was attenuated compared with the passive listening in quiet. Taken together, these results demonstrate that top-down attention differentially modulates envelope-tracking neural activity at different time lags and suggest that top-down attention can both enhance the neural responses to the attended sound stream and suppress the responses to the unattended sound stream. PMID:25124153
Neural correlates of inhibitory control in adult ADHD: Evidence from the Milwaukee longitudinal sample

PubMed Central

Mulligan, Richard C.; Knopik, Valerie S.; Sweet, Lawrence H.; Fischer, Mariellen; Seidenberg, Michael; Rao, Stephen M.

2011-01-01

Only a few studies have investigated the neural substrate of response inhibition in adult ADHD using Stop-Signal and Go/No-Go tasks. Inconsistencies and methodological limitations in the existing literature have resulted in limited conclusions regarding underlying pathophysiology. We examined the neural basis of response inhibition in a group of adults diagnosed with ADHD in childhood and who continue to meet criteria for ADHD while addressing limitations present in earlier studies. Adults with ADHD (n=12) and controls (n=12) were recruited from an ongoing longitudinal study and were matched for age, IQ, and education. Individuals with comorbid conditions were excluded. Functional MRI was used to identify and compare the brain activation patterns during correct trials of a response inhibition task (Go/No-Go). Our results showed that the control group recruited a more extensive network of brain regions than the ADHD group during correct inhibition trials. Adults with ADHD showed reduced brain activation in the right frontal eye field, pre-supplementary motor area, left precentral gyrus, and the inferior parietal lobe bilaterally. During successful inhibition of an inappropriate response, adults with ADHD display reduced activation in fronto-parietal networks previously implicated in working memory, goal-oriented attention, and response selection. This profile of brain activation may be specifically associated with ADHD in adulthood. PMID:21937201
Dynamics of Multistable States during Ongoing and Evoked Cortical Activity

PubMed Central

Mazzucato, Luca

2015-01-01

Single-trial analyses of ensemble activity in alert animals demonstrate that cortical circuits dynamics evolve through temporal sequences of metastable states. Metastability has been studied for its potential role in sensory coding, memory, and decision-making. Yet, very little is known about the network mechanisms responsible for its genesis. It is often assumed that the onset of state sequences is triggered by an external stimulus. Here we show that state sequences can be observed also in the absence of overt sensory stimulation. Analysis of multielectrode recordings from the gustatory cortex of alert rats revealed ongoing sequences of states, where single neurons spontaneously attain several firing rates across different states. This single-neuron multistability represents a challenge to existing spiking network models, where typically each neuron is at most bistable. We present a recurrent spiking network model that accounts for both the spontaneous generation of state sequences and the multistability in single-neuron firing rates. Each state results from the activation of neural clusters with potentiated intracluster connections, with the firing rate in each cluster depending on the number of active clusters. Simulations show that the model's ensemble activity hops among the different states, reproducing the ongoing dynamics observed in the data. When probed with external stimuli, the model predicts the quenching of single-neuron multistability into bistability and the reduction of trial-by-trial variability. Both predictions were confirmed in the data. Together, these results provide a theoretical framework that captures both ongoing and evoked network dynamics in a single mechanistic model. PMID:26019337
Bridging from Cells to Cognition in Autism Pathophysiology: Biological Pathways to Defective Brain Function and Plasticity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, Matthew; Hooker, Brian S.; Herbert, Martha

We review evidence to support the model that autism may begin when a maternal environmental, infectious, or autoantibody insult causes inflammation which increases reactive oxygen species (ROS) production in the fetus, leading to fetal DNA damage (nuclear and mitochondrial), and that these inflammatory and oxidative stressors persist beyond early development (with potential further exacerbations), producing ongoing functional consequences. In organs with a high metabolic demand such as the central nervous system, the continued use of mitochondria with DNA damage may generate additional ROS which will activate the innate immune system leading to more ROS production. Such a mechanism would self-sustainmore » and possibly progressively worsen. The mitochondrial dysfunction and altered redox signal transduction pathways found in autism would conspire to activate both astroglia and microglia. These activated cells can then initiate a broad-spectrum proinflammatory gene response. Neurons may have acquired receptors for these inflammatory signals to inhibit neuronal signaling as a protection from excitotoxic damage during various pathologic insults (e.g., infection). In autism, over-zealous neuroinflammatory responses could not only influence neural developmental processes, but may more significantly impair neural signaling involved in cognition in an ongoing fashion. This model makes specific predictions in patients and experimental animal models and suggests a number of targets sites of intervention. Our model of potentially reversible pathophysiological mechanisms in autism motivates our hope that effective therapies may soon appear on the horizon.« less
The relationship between level of processing and hippocampal-cortical functional connectivity during episodic memory formation in humans.

PubMed

Schott, Björn H; Wüstenberg, Torsten; Wimber, Maria; Fenker, Daniela B; Zierhut, Kathrin C; Seidenbecher, Constanze I; Heinze, Hans-Jochen; Walter, Henrik; Düzel, Emrah; Richardson-Klavehn, Alan

2013-02-01

New episodic memory traces represent a record of the ongoing neocortical processing engaged during memory formation (encoding). Thus, during encoding, deep (semantic) processing typically establishes more distinctive and retrievable memory traces than does shallow (perceptual) processing, as assessed by later episodic memory tests. By contrast, the hippocampus appears to play a processing-independent role in encoding, because hippocampal lesions impair encoding regardless of level of processing. Here, we clarified the neural relationship between processing and encoding by examining hippocampal-cortical connectivity during deep and shallow encoding. Participants studied words during functional magnetic resonance imaging and freely recalled these words after distraction. Deep study processing led to better recall than shallow study processing. For both levels of processing, successful encoding elicited activations of bilateral hippocampus and left prefrontal cortex, and increased functional connectivity between left hippocampus and bilateral medial prefrontal, cingulate and extrastriate cortices. Successful encoding during deep processing was additionally associated with increased functional connectivity between left hippocampus and bilateral ventrolateral prefrontal cortex and right temporoparietal junction. In the shallow encoding condition, on the other hand, pronounced functional connectivity increases were observed between the right hippocampus and the frontoparietal attention network activated during shallow study processing. Our results further specify how the hippocampus coordinates recording of ongoing neocortical activity into long-term memory, and begin to provide a neural explanation for the typical advantage of deep over shallow study processing for later episodic memory. Copyright © 2011 Wiley Periodicals, Inc.
Using Biophysical Models to Understand the Effect of tDCS on Neurorehabilitation: Searching for Optimal Covariates to Enhance Poststroke Recovery

PubMed Central

Malerba, Paola; Straudi, Sofia; Fregni, Felipe; Bazhenov, Maxim; Basaglia, Nino

2017-01-01

Stroke is a leading cause of worldwide disability, and up to 75% of survivors suffer from some degree of arm paresis. Recently, rehabilitation of stroke patients has focused on recovering motor skills by taking advantage of use-dependent neuroplasticity, where high-repetition of goal-oriented movement is at times combined with non-invasive brain stimulation, such as transcranial direct current stimulation (tDCS). Merging the two approaches is thought to provide outlasting clinical gains, by enhancing synaptic plasticity and motor relearning in the motor cortex primary area. However, this general approach has shown mixed results across the stroke population. In particular, stroke location has been found to correlate with the likelihood of success, which suggests that different patients might require different protocols. Understanding how motor rehabilitation and stimulation interact with ongoing neural dynamics is crucial to optimize rehabilitation strategies, but it requires theoretical and computational models to consider the multiple levels at which this complex phenomenon operate. In this work, we argue that biophysical models of cortical dynamics are uniquely suited to address this problem. Specifically, biophysical models can predict treatment efficacy by introducing explicit variables and dynamics for damaged connections, changes in neural excitability, neurotransmitters, neuromodulators, plasticity mechanisms, and repetitive movement, which together can represent brain state, effect of incoming stimulus, and movement-induced activity. In this work, we hypothesize that effects of tDCS depend on ongoing neural activity and that tDCS effects on plasticity may be also related to enhancing inhibitory processes. We propose a model design for each step of this complex system, and highlight strengths and limitations of the different modeling choices within our approach. Our theoretical framework proposes a change in paradigm, where biophysical models can contribute to the future design of novel protocols, in which combined tDCS and motor rehabilitation strategies are tailored to the ongoing dynamics that they interact with, by considering the known biophysical factors recruited by such protocols and their interaction. PMID:28280482
Salient sounds activate human visual cortex automatically.

PubMed

McDonald, John J; Störmer, Viola S; Martinez, Antigona; Feng, Wenfeng; Hillyard, Steven A

2013-05-22

Sudden changes in the acoustic environment enhance perceptual processing of subsequent visual stimuli that appear in close spatial proximity. Little is known, however, about the neural mechanisms by which salient sounds affect visual processing. In particular, it is unclear whether such sounds automatically activate visual cortex. To shed light on this issue, this study examined event-related brain potentials (ERPs) that were triggered either by peripheral sounds that preceded task-relevant visual targets (Experiment 1) or were presented during purely auditory tasks (Experiments 2-4). In all experiments the sounds elicited a contralateral ERP over the occipital scalp that was localized to neural generators in extrastriate visual cortex of the ventral occipital lobe. The amplitude of this cross-modal ERP was predictive of perceptual judgments about the contrast of colocalized visual targets. These findings demonstrate that sudden, intrusive sounds reflexively activate human visual cortex in a spatially specific manner, even during purely auditory tasks when the sounds are not relevant to the ongoing task.
Salient sounds activate human visual cortex automatically

PubMed Central

McDonald, John J.; Störmer, Viola S.; Martinez, Antigona; Feng, Wenfeng; Hillyard, Steven A.

2013-01-01

Sudden changes in the acoustic environment enhance perceptual processing of subsequent visual stimuli that appear in close spatial proximity. Little is known, however, about the neural mechanisms by which salient sounds affect visual processing. In particular, it is unclear whether such sounds automatically activate visual cortex. To shed light on this issue, the present study examined event-related brain potentials (ERPs) that were triggered either by peripheral sounds that preceded task-relevant visual targets (Experiment 1) or were presented during purely auditory tasks (Experiments 2, 3, and 4). In all experiments the sounds elicited a contralateral ERP over the occipital scalp that was localized to neural generators in extrastriate visual cortex of the ventral occipital lobe. The amplitude of this cross-modal ERP was predictive of perceptual judgments about the contrast of co-localized visual targets. These findings demonstrate that sudden, intrusive sounds reflexively activate human visual cortex in a spatially specific manner, even during purely auditory tasks when the sounds are not relevant to the ongoing task. PMID:23699530
Alteration of neural action potential patterns by axonal stimulation: the importance of stimulus location

PubMed Central

Crago, Patrick E; Makowski, Nathan S

2014-01-01

Objective Stimulation of peripheral nerves is often superimposed on ongoing motor and sensory activity in the same axons, without a quantitative model of the net action potential train at the axon endpoint. Approach We develop a model of action potential patterns elicited by superimposing constant frequency axonal stimulation on the action potentials arriving from a physiologically activated neural source. The model includes interactions due to collision block, resetting of the neural impulse generator, and the refractory period of the axon at the point of stimulation. Main Results Both the mean endpoint firing rate and the probability distribution of the action potential firing periods depend strongly on the relative firing rates of the two sources and the intersite conduction time between them. When the stimulus rate exceeds the neural rate, neural action potentials do not reach the endpoint and the rate of endpoint action potentials is the same as the stimulus rate, regardless of the intersite conduction time. However, when the stimulus rate is less than the neural rate, and the intersite conduction time is short, the two rates partially sum. Increases in stimulus rate produce non-monotonic increases in endpoint rate and continuously increasing block of neurally generated action potentials. Rate summation is reduced and more neural action potentials are blocked as the intersite conduction time increases.. At long intersite conduction times, the endpoint rate simplifies to being the maximum of either the neural or the stimulus rate. Significance This study highlights the potential of increasing the endpoint action potential rate and preserving neural information transmission by low rate stimulation with short intersite conduction times. Intersite conduction times can be decreased with proximal stimulation sites for muscles and distal stimulation sites for sensory endings. The model provides a basis for optimizing experiments and designing neuroprosthetic interventions involving motor or sensory stimulation. PMID:25161163

Alteration of neural action potential patterns by axonal stimulation: the importance of stimulus location

NASA Astrophysics Data System (ADS)

Crago, Patrick E.; Makowski, Nathaniel S.

2014-10-01

Objective. Stimulation of peripheral nerves is often superimposed on ongoing motor and sensory activity in the same axons, without a quantitative model of the net action potential train at the axon endpoint. Approach. We develop a model of action potential patterns elicited by superimposing constant frequency axonal stimulation on the action potentials arriving from a physiologically activated neural source. The model includes interactions due to collision block, resetting of the neural impulse generator, and the refractory period of the axon at the point of stimulation. Main results. Both the mean endpoint firing rate and the probability distribution of the action potential firing periods depend strongly on the relative firing rates of the two sources and the intersite conduction time between them. When the stimulus rate exceeds the neural rate, neural action potentials do not reach the endpoint and the rate of endpoint action potentials is the same as the stimulus rate, regardless of the intersite conduction time. However, when the stimulus rate is less than the neural rate, and the intersite conduction time is short, the two rates partially sum. Increases in stimulus rate produce non-monotonic increases in endpoint rate and continuously increasing block of neurally generated action potentials. Rate summation is reduced and more neural action potentials are blocked as the intersite conduction time increases. At long intersite conduction times, the endpoint rate simplifies to being the maximum of either the neural or the stimulus rate. Significance. This study highlights the potential of increasing the endpoint action potential rate and preserving neural information transmission by low rate stimulation with short intersite conduction times. Intersite conduction times can be decreased with proximal stimulation sites for muscles and distal stimulation sites for sensory endings. The model provides a basis for optimizing experiments and designing neuroprosthetic interventions involving motor or sensory stimulation.
Learning by subtraction: Hippocampal activity and effects of ethanol during the acquisition and performance of response sequences.

PubMed

Ketchum, Myles J; Weyand, Theodore G; Weed, Peter F; Winsauer, Peter J

2016-05-01

Learning is believed to be reflected in the activity of the hippocampus. However, neural correlates of learning have been difficult to characterize because hippocampal activity is integrated with ongoing behavior. To address this issue, male rats (n = 5) implanted with electrodes (n = 14) in the CA1 subfield responded during two tasks within a single test session. In one task, subjects acquired a new 3-response sequence (acquisition), whereas in the other task, subjects completed a well-rehearsed 3-response sequence (performance). Both tasks though could be completed using an identical response topography and used the same sensory stimuli and schedule of reinforcement. More important, comparing neural patterns during sequence acquisition to those during sequence performance allows for a subtractive approach whereby activity associated with learning could potentially be dissociated from the activity associated with ongoing behavior. At sites where CA1 activity was closely associated with behavior, the patterns of activity were differentially modulated by key position and the serial position of a response within the schedule of reinforcement. Temporal shifts between peak activity and responding on particular keys also occurred during sequence acquisition, but not during sequence performance. Ethanol disrupted CA1 activity while producing rate-decreasing effects in both tasks and error-increasing effects that were more selective for sequence acquisition than sequence performance. Ethanol also produced alterations in the magnitude of modulations and temporal pattern of CA1 activity, although these effects were not selective for sequence acquisition. Similar to ethanol, hippocampal micro-stimulation decreased response rate in both tasks and selectively increased the percentage of errors during sequence acquisition, and provided a more direct demonstration of hippocampal involvement during sequence acquisition. Together, these results strongly support the notion that ethanol disrupts sequence acquisition by disrupting hippocampal activity and that the hippocampus is necessary for the conditioned associations required for sequence acquisition. © 2015 Wiley Periodicals, Inc.
Learning by Subtraction: Hippocampal Activity and Effects of Ethanol during the Acquisition and Performance of Response Sequences

PubMed Central

Ketchum, Myles J.; Weyand, Theodore G.; Weed, Peter F.; Winsauer, Peter J.

2015-01-01

Learning is believed to be reflected in the activity of the hippocampus. However, neural correlates of learning have been difficult to characterize because hippocampal activity is integrated with ongoing behavior. To address this issue, male rats (n=5) implanted with electrodes (n=14) in the CA1 subfield responded during two tasks within a single test session. In one task, subjects acquired a new 3-response sequence (acquisition), whereas in the other task, subjects completed a well-rehearsed 3-response sequence (performance). Both tasks though could be completed using an identical response topography and used the same sensory stimuli and schedule of reinforcement. More important, comparing neural patterns during sequence acquisition to those during sequence performance allows for a subtractive approach whereby activity associated with learning could potentially be dissociated from the activity associated with ongoing behavior. At sites where CA1 activity was closely associated with behavior, the patterns of activity were differentially modulated by key position and the serial position of a response within the schedule of reinforcement. Temporal shifts between peak activity and responding on particular keys also occurred during sequence acquisition, but not during sequence performance. Ethanol disrupted CA1 activity while producing rate-decreasing effects in both tasks and error-increasing effects that were more selective for sequence acquisition than sequence performance. Ethanol also produced alterations in the magnitude of modulations and temporal pattern of CA1 activity, although these effects were not selective for sequence acquisition. Similar to ethanol, hippocampal micro-stimulation decreased response rate in both tasks and selectively increased the percentage of errors during sequence acquisition, and provided a more direct demonstration of hippocampal involvement during sequence acquisition. Together, these results strongly support the notion that ethanol disrupts sequence acquisition by disrupting hippocampal activity and that the hippocampus is necessary for the conditioned associations required for sequence acquisition. PMID:26482846
Phase-Locked Responses to Speech in Human Auditory Cortex are Enhanced During Comprehension

PubMed Central

Peelle, Jonathan E.; Gross, Joachim; Davis, Matthew H.

2013-01-01

A growing body of evidence shows that ongoing oscillations in auditory cortex modulate their phase to match the rhythm of temporally regular acoustic stimuli, increasing sensitivity to relevant environmental cues and improving detection accuracy. In the current study, we test the hypothesis that nonsensory information provided by linguistic content enhances phase-locked responses to intelligible speech in the human brain. Sixteen adults listened to meaningful sentences while we recorded neural activity using magnetoencephalography. Stimuli were processed using a noise-vocoding technique to vary intelligibility while keeping the temporal acoustic envelope consistent. We show that the acoustic envelopes of sentences contain most power between 4 and 7 Hz and that it is in this frequency band that phase locking between neural activity and envelopes is strongest. Bilateral oscillatory neural activity phase-locked to unintelligible speech, but this cerebro-acoustic phase locking was enhanced when speech was intelligible. This enhanced phase locking was left lateralized and localized to left temporal cortex. Together, our results demonstrate that entrainment to connected speech does not only depend on acoustic characteristics, but is also affected by listeners’ ability to extract linguistic information. This suggests a biological framework for speech comprehension in which acoustic and linguistic cues reciprocally aid in stimulus prediction. PMID:22610394
Phase-locked responses to speech in human auditory cortex are enhanced during comprehension.

PubMed

Peelle, Jonathan E; Gross, Joachim; Davis, Matthew H

2013-06-01

A growing body of evidence shows that ongoing oscillations in auditory cortex modulate their phase to match the rhythm of temporally regular acoustic stimuli, increasing sensitivity to relevant environmental cues and improving detection accuracy. In the current study, we test the hypothesis that nonsensory information provided by linguistic content enhances phase-locked responses to intelligible speech in the human brain. Sixteen adults listened to meaningful sentences while we recorded neural activity using magnetoencephalography. Stimuli were processed using a noise-vocoding technique to vary intelligibility while keeping the temporal acoustic envelope consistent. We show that the acoustic envelopes of sentences contain most power between 4 and 7 Hz and that it is in this frequency band that phase locking between neural activity and envelopes is strongest. Bilateral oscillatory neural activity phase-locked to unintelligible speech, but this cerebro-acoustic phase locking was enhanced when speech was intelligible. This enhanced phase locking was left lateralized and localized to left temporal cortex. Together, our results demonstrate that entrainment to connected speech does not only depend on acoustic characteristics, but is also affected by listeners' ability to extract linguistic information. This suggests a biological framework for speech comprehension in which acoustic and linguistic cues reciprocally aid in stimulus prediction.
Content-specific coordination of listeners' to speakers' EEG during communication.

PubMed

Kuhlen, Anna K; Allefeld, Carsten; Haynes, John-Dylan

2012-01-01

Cognitive neuroscience has recently begun to extend its focus from the isolated individual mind to two or more individuals coordinating with each other. In this study we uncover a coordination of neural activity between the ongoing electroencephalogram (EEG) of two people-a person speaking and a person listening. The EEG of one set of twelve participants ("speakers") was recorded while they were narrating short stories. The EEG of another set of twelve participants ("listeners") was recorded while watching audiovisual recordings of these stories. Specifically, listeners watched the superimposed videos of two speakers simultaneously and were instructed to attend either to one or the other speaker. This allowed us to isolate neural coordination due to processing the communicated content from the effects of sensory input. We find several neural signatures of communication: First, the EEG is more similar among listeners attending to the same speaker than among listeners attending to different speakers, indicating that listeners' EEG reflects content-specific information. Secondly, listeners' EEG activity correlates with the attended speakers' EEG, peaking at a time delay of about 12.5 s. This correlation takes place not only between homologous, but also between non-homologous brain areas in speakers and listeners. A semantic analysis of the stories suggests that listeners coordinate with speakers at the level of complex semantic representations, so-called "situation models". With this study we link a coordination of neural activity between individuals directly to verbally communicated information.
Content-specific coordination of listeners' to speakers' EEG during communication

PubMed Central

Kuhlen, Anna K.; Allefeld, Carsten; Haynes, John-Dylan

2012-01-01

Cognitive neuroscience has recently begun to extend its focus from the isolated individual mind to two or more individuals coordinating with each other. In this study we uncover a coordination of neural activity between the ongoing electroencephalogram (EEG) of two people—a person speaking and a person listening. The EEG of one set of twelve participants (“speakers”) was recorded while they were narrating short stories. The EEG of another set of twelve participants (“listeners”) was recorded while watching audiovisual recordings of these stories. Specifically, listeners watched the superimposed videos of two speakers simultaneously and were instructed to attend either to one or the other speaker. This allowed us to isolate neural coordination due to processing the communicated content from the effects of sensory input. We find several neural signatures of communication: First, the EEG is more similar among listeners attending to the same speaker than among listeners attending to different speakers, indicating that listeners' EEG reflects content-specific information. Secondly, listeners' EEG activity correlates with the attended speakers' EEG, peaking at a time delay of about 12.5 s. This correlation takes place not only between homologous, but also between non-homologous brain areas in speakers and listeners. A semantic analysis of the stories suggests that listeners coordinate with speakers at the level of complex semantic representations, so-called “situation models”. With this study we link a coordination of neural activity between individuals directly to verbally communicated information. PMID:23060770
Neural control of cursor trajectory and click by a human with tetraplegia 1000 days after implant of an intracortical microelectrode array

NASA Astrophysics Data System (ADS)

Simeral, J. D.; Kim, S.-P.; Black, M. J.; Donoghue, J. P.; Hochberg, L. R.

2011-04-01

The ongoing pilot clinical trial of the BrainGate neural interface system aims in part to assess the feasibility of using neural activity obtained from a small-scale, chronically implanted, intracortical microelectrode array to provide control signals for a neural prosthesis system. Critical questions include how long implanted microelectrodes will record useful neural signals, how reliably those signals can be acquired and decoded, and how effectively they can be used to control various assistive technologies such as computers and robotic assistive devices, or to enable functional electrical stimulation of paralyzed muscles. Here we examined these questions by assessing neural cursor control and BrainGate system characteristics on five consecutive days 1000 days after implant of a 4 × 4 mm array of 100 microelectrodes in the motor cortex of a human with longstanding tetraplegia subsequent to a brainstem stroke. On each of five prospectively-selected days we performed time-amplitude sorting of neuronal spiking activity, trained a population-based Kalman velocity decoding filter combined with a linear discriminant click state classifier, and then assessed closed-loop point-and-click cursor control. The participant performed both an eight-target center-out task and a random target Fitts metric task which was adapted from a human-computer interaction ISO standard used to quantify performance of computer input devices. The neural interface system was further characterized by daily measurement of electrode impedances, unit waveforms and local field potentials. Across the five days, spiking signals were obtained from 41 of 96 electrodes and were successfully decoded to provide neural cursor point-and-click control with a mean task performance of 91.3% ± 0.1% (mean ± s.d.) correct target acquisition. Results across five consecutive days demonstrate that a neural interface system based on an intracortical microelectrode array can provide repeatable, accurate point-and-click control of a computer interface to an individual with tetraplegia 1000 days after implantation of this sensor.
Neural control of cursor trajectory and click by a human with tetraplegia 1000 days after implant of an intracortical microelectrode array

PubMed Central

Simeral, J D; Kim, S-P; Black, M J; Donoghue, J P; Hochberg, L R

2013-01-01

The ongoing pilot clinical trial of the BrainGate neural interface system aims in part to assess the feasibility of using neural activity obtained from a small-scale, chronically implanted, intracortical microelectrode array to provide control signals for a neural prosthesis system. Critical questions include how long implanted microelectrodes will record useful neural signals, how reliably those signals can be acquired and decoded, and how effectively they can be used to control various assistive technologies such as computers and robotic assistive devices, or to enable functional electrical stimulation of paralyzed muscles. Here we examined these questions by assessing neural cursor control and BrainGate system characteristics on five consecutive days 1000 days after implant of a 4 × 4 mm array of 100 microelectrodes in the motor cortex of a human with longstanding tetraplegia subsequent to a brainstem stroke. On each of five prospectively-selected days we performed time-amplitude sorting of neuronal spiking activity, trained a population-based Kalman velocity decoding filter combined with a linear discriminant click state classifier, and then assessed closed-loop point-and-click cursor control. The participant performed both an eight-target center-out task and a random target Fitts metric task which was adapted from a human-computer interaction ISO standard used to quantify performance of computer input devices. The neural interface system was further characterized by daily measurement of electrode impedances, unit waveforms and local field potentials. Across the five days, spiking signals were obtained from 41 of 96 electrodes and were successfully decoded to provide neural cursor point-and-click control with a mean task performance of 91.3% ± 0.1% (mean ± s.d.) correct target acquisition. Results across five consecutive days demonstrate that a neural interface system based on an intracortical microelectrode array can provide repeatable, accurate point-and-click control of a computer interface to an individual with tetraplegia 1000 days after implantation of this sensor. PMID:21436513
Pulsed Out of Awareness: EEG Alpha Oscillations Represent a Pulsed-Inhibition of Ongoing Cortical Processing

PubMed Central

Mathewson, Kyle E.; Lleras, Alejandro; Beck, Diane M.; Fabiani, Monica; Ro, Tony; Gratton, Gabriele

2011-01-01

Alpha oscillations are ubiquitous in the brain, but their role in cortical processing remains a matter of debate. Recently, evidence has begun to accumulate in support of a role for alpha oscillations in attention selection and control. Here we first review evidence that 8–12 Hz oscillations in the brain have a general inhibitory role in cognitive processing, with an emphasis on their role in visual processing. Then, we summarize the evidence in support of our recent proposal that alpha represents a pulsed-inhibition of ongoing neural activity. The phase of the ongoing electroencephalography can influence evoked activity and subsequent processing, and we propose that alpha exerts its inhibitory role through alternating microstates of inhibition and excitation. Finally, we discuss evidence that this pulsed-inhibition can be entrained to rhythmic stimuli in the environment, such that preferential processing occurs for stimuli at predictable moments. The entrainment of preferential phase may provide a mechanism for temporal attention in the brain. This pulsed inhibitory account of alpha has important implications for many common cognitive phenomena, such as the attentional blink, and seems to indicate that our visual experience may at least some times be coming through in waves. PMID:21779257
Unreliable evoked responses in autism

PubMed Central

Dinstein, Ilan; Heeger, David J.; Lorenzi, Lauren; Minshew, Nancy J.; Malach, Rafael; Behrmann, Marlene

2012-01-01

Summary Autism has been described as a disorder of general neural processing, but the particular processing characteristics that might be abnormal in autism have mostly remained obscure. Here, we present evidence of one such characteristic: poor evoked response reliability. We compared cortical response amplitude and reliability (consistency across trials) in visual, auditory, and somatosensory cortices of high-functioning individuals with autism and controls. Mean response amplitudes were statistically indistinguishable across groups, yet trial-by-trial response reliability was significantly weaker in autism, yielding smaller signal-to-noise ratios in all sensory systems. Response reliability differences were evident only in evoked cortical responses and not in ongoing resting-state activity. These findings reveal that abnormally unreliable cortical responses, even to elementary non-social sensory stimuli, may represent a fundamental physiological alteration of neural processing in autism. The results motivate a critical expansion of autism research to determine whether (and how) basic neural processing properties such as reliability, plasticity, and adaptation/habituation are altered in autism. PMID:22998867
Neuropsychopharmacology of auditory hallucinations: insights from pharmacological functional MRI and perspectives for future research.

PubMed

Johnsen, Erik; Hugdahl, Kenneth; Fusar-Poli, Paolo; Kroken, Rune A; Kompus, Kristiina

2013-01-01

Experiencing auditory verbal hallucinations is a prominent symptom in schizophrenia that also occurs in subjects at enhanced risk for psychosis and in the general population. Drug treatment of auditory hallucinations is challenging, because the current understanding is limited with respect to the neural mechanisms involved, as well as how CNS drugs, such as antipsychotics, influence the subjective experience and neurophysiology of hallucinations. In this article, the authors review studies of the effect of antipsychotic medication on brain activation as measured with functional MRI in patients with auditory verbal hallucinations. First, the authors examine the neural correlates of ongoing auditory hallucinations. Then, the authors critically discuss studies addressing the antipsychotic effect on the neural correlates of complex cognitive tasks. Current evidence suggests that blood oxygen level-dependant effects of antipsychotic drugs reflect specific, regional effects but studies on the neuropharmacology of auditory hallucinations are scarce. Future directions for pharmacological neuroimaging of auditory hallucinations are discussed.
Application of neural nets in structural optimization

NASA Technical Reports Server (NTRS)

Berke, Laszlo; Hajela, Prabhat

1993-01-01

The biological motivation for Artificial Neural Net developments is briefly discussed, and the most popular paradigm, the feedforward supervised learning net with error back propagation training algorithm, is introduced. Possible approaches for utilization in structural optimization is illustrated through simple examples. Other currently ongoing developments for application in structural mechanics are also mentioned.
Subcortical processing of speech regularities underlies reading and music aptitude in children.

PubMed

Strait, Dana L; Hornickel, Jane; Kraus, Nina

2011-10-17

Neural sensitivity to acoustic regularities supports fundamental human behaviors such as hearing in noise and reading. Although the failure to encode acoustic regularities in ongoing speech has been associated with language and literacy deficits, how auditory expertise, such as the expertise that is associated with musical skill, relates to the brainstem processing of speech regularities is unknown. An association between musical skill and neural sensitivity to acoustic regularities would not be surprising given the importance of repetition and regularity in music. Here, we aimed to define relationships between the subcortical processing of speech regularities, music aptitude, and reading abilities in children with and without reading impairment. We hypothesized that, in combination with auditory cognitive abilities, neural sensitivity to regularities in ongoing speech provides a common biological mechanism underlying the development of music and reading abilities. We assessed auditory working memory and attention, music aptitude, reading ability, and neural sensitivity to acoustic regularities in 42 school-aged children with a wide range of reading ability. Neural sensitivity to acoustic regularities was assessed by recording brainstem responses to the same speech sound presented in predictable and variable speech streams. Through correlation analyses and structural equation modeling, we reveal that music aptitude and literacy both relate to the extent of subcortical adaptation to regularities in ongoing speech as well as with auditory working memory and attention. Relationships between music and speech processing are specifically driven by performance on a musical rhythm task, underscoring the importance of rhythmic regularity for both language and music. These data indicate common brain mechanisms underlying reading and music abilities that relate to how the nervous system responds to regularities in auditory input. Definition of common biological underpinnings for music and reading supports the usefulness of music for promoting child literacy, with the potential to improve reading remediation.
Efficient Decoding With Steady-State Kalman Filter in Neural Interface Systems

PubMed Central

Malik, Wasim Q.; Truccolo, Wilson; Brown, Emery N.; Hochberg, Leigh R.

2011-01-01

The Kalman filter is commonly used in neural interface systems to decode neural activity and estimate the desired movement kinematics. We analyze a low-complexity Kalman filter implementation in which the filter gain is approximated by its steady-state form, computed offline before real-time decoding commences. We evaluate its performance using human motor cortical spike train data obtained from an intracortical recording array as part of an ongoing pilot clinical trial. We demonstrate that the standard Kalman filter gain converges to within 95% of the steady-state filter gain in 1.5 ± 0.5 s (mean ± s.d.). The difference in the intended movement velocity decoded by the two filters vanishes within 5 s, with a correlation coefficient of 0.99 between the two decoded velocities over the session length. We also find that the steady-state Kalman filter reduces the computational load (algorithm execution time) for decoding the firing rates of 25 ± 3 single units by a factor of 7.0 ± 0.9. We expect that the gain in computational efficiency will be much higher in systems with larger neural ensembles. The steady-state filter can thus provide substantial runtime efficiency at little cost in terms of estimation accuracy. This far more efficient neural decoding approach will facilitate the practical implementation of future large-dimensional, multisignal neural interface systems. PMID:21078582
Feedback control stabilization of critical dynamics via resource transport on multilayer networks: How glia enable learning dynamics in the brain

NASA Astrophysics Data System (ADS)

Virkar, Yogesh S.; Shew, Woodrow L.; Restrepo, Juan G.; Ott, Edward

2016-10-01

Learning and memory are acquired through long-lasting changes in synapses. In the simplest models, such synaptic potentiation typically leads to runaway excitation, but in reality there must exist processes that robustly preserve overall stability of the neural system dynamics. How is this accomplished? Various approaches to this basic question have been considered. Here we propose a particularly compelling and natural mechanism for preserving stability of learning neural systems. This mechanism is based on the global processes by which metabolic resources are distributed to the neurons by glial cells. Specifically, we introduce and study a model composed of two interacting networks: a model neural network interconnected by synapses that undergo spike-timing-dependent plasticity; and a model glial network interconnected by gap junctions that diffusively transport metabolic resources among the glia and, ultimately, to neural synapses where they are consumed. Our main result is that the biophysical constraints imposed by diffusive transport of metabolic resources through the glial network can prevent runaway growth of synaptic strength, both during ongoing activity and during learning. Our findings suggest a previously unappreciated role for glial transport of metabolites in the feedback control stabilization of neural network dynamics during learning.
A generalized locomotion CPG architecture based on oscillatory building blocks.

PubMed

Yang, Zhijun; França, Felipe M G

2003-07-01

Neural oscillation is one of the most extensively investigated topics of artificial neural networks. Scientific approaches to the functionalities of both natural and artificial intelligences are strongly related to mechanisms underlying oscillatory activities. This paper concerns itself with the assumption of the existence of central pattern generators (CPGs), which are the plausible neural architectures with oscillatory capabilities, and presents a discrete and generalized approach to the functionality of locomotor CPGs of legged animals. Based on scheduling by multiple edge reversal (SMER), a primitive and deterministic distributed algorithm, it is shown how oscillatory building block (OBB) modules can be created and, hence, how OBB-based networks can be formulated as asymmetric Hopfield-like neural networks for the generation of complex coordinated rhythmic patterns observed among pairs of biological motor neurons working during different gait patterns. It is also shown that the resulting Hopfield-like network possesses the property of reproducing the whole spectrum of different gaits intrinsic to the target locomotor CPGs. Although the new approach is not restricted to the understanding of the neurolocomotor system of any particular animal, hexapodal and quadrupedal gait patterns are chosen as illustrations given the wide interest expressed by the ongoing research in the area.
Homeostatic Scaling of Excitability in Recurrent Neural Networks

PubMed Central

Remme, Michiel W. H.; Wadman, Wytse J.

2012-01-01

Neurons adjust their intrinsic excitability when experiencing a persistent change in synaptic drive. This process can prevent neural activity from moving into either a quiescent state or a saturated state in the face of ongoing plasticity, and is thought to promote stability of the network in which neurons reside. However, most neurons are embedded in recurrent networks, which require a delicate balance between excitation and inhibition to maintain network stability. This balance could be disrupted when neurons independently adjust their intrinsic excitability. Here, we study the functioning of activity-dependent homeostatic scaling of intrinsic excitability (HSE) in a recurrent neural network. Using both simulations of a recurrent network consisting of excitatory and inhibitory neurons that implement HSE, and a mean-field description of adapting excitatory and inhibitory populations, we show that the stability of such adapting networks critically depends on the relationship between the adaptation time scales of both neuron populations. In a stable adapting network, HSE can keep all neurons functioning within their dynamic range, while the network is undergoing several (patho)physiologically relevant types of plasticity, such as persistent changes in external drive, changes in connection strengths, or the loss of inhibitory cells from the network. However, HSE cannot prevent the unstable network dynamics that result when, due to such plasticity, recurrent excitation in the network becomes too strong compared to feedback inhibition. This suggests that keeping a neural network in a stable and functional state requires the coordination of distinct homeostatic mechanisms that operate not only by adjusting neural excitability, but also by controlling network connectivity. PMID:22570604
A 3D Active Learning Application for NeMO-Net, the NASA Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

NASA Technical Reports Server (NTRS)

van den Bergh, Jarrett; Schutz, Joey; Li, Alan; Chirayath, Ved

2017-01-01

NeMO-Net, the NASA neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive video game prototype for tablet and mobile devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using fluid lensing to create a dataset that will be used to train NeMO-Nets convolutional neural network. The application currently allows for users to classify preselected regions of coral in the Pacific and will be expanded to include additional regions captured using our NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as lower-resolution airborne remote sensing data from the ongoing NASA CORAL campaign. Active learning applications present a novel methodology for efficiently training large-scale Neural Networks wherein variances in identification can be rapidly mitigated against control data. NeMO-Net periodically checks users input against pre-classified coral imagery to gauge their accuracy and utilize in-game mechanics to provide classification training. Users actively communicate with a server and are requested to classify areas of coral for which other users had conflicting classifications and contribute their input to a larger database for ranking. In partnering with Mission Blue and IUCN, NeMO-Net leverages an international consortium of subject matter experts to classify areas of confusion identified by NeMO-Net and generate additional labels crucial for identifying decision boundary locations in coral reef assessment.
A 3D Active Learning Application for NeMO-Net, the NASA Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

NASA Astrophysics Data System (ADS)

van den Bergh, J.; Schutz, J.; Chirayath, V.; Li, A.

2017-12-01

NeMO-Net, the NASA neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive video game prototype for tablet and mobile devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using fluid lensing to create a dataset that will be used to train NeMO-Net's convolutional neural network. The application currently allows for users to classify preselected regions of coral in the Pacific and will be expanded to include additional regions captured using our NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as lower-resolution airborne remote sensing data from the ongoing NASA CORAL campaign.Active learning applications present a novel methodology for efficiently training large-scale Neural Networks wherein variances in identification can be rapidly mitigated against control data. NeMO-Net periodically checks users' input against pre-classified coral imagery to gauge their accuracy and utilizes in-game mechanics to provide classification training. Users actively communicate with a server and are requested to classify areas of coral for which other users had conflicting classifications and contribute their input to a larger database for ranking. In partnering with Mission Blue and IUCN, NeMO-Net leverages an international consortium of subject matter experts to classify areas of confusion identified by NeMO-Net and generate additional labels crucial for identifying decision boundary locations in coral reef assessment.

Ongoing neural development of affective theory of mind in adolescence

PubMed Central

Weigelt, Sarah; Döhnel, Katrin; Smolka, Michael N.; Kliegel, Matthias

2014-01-01

Affective Theory of Mind (ToM), an important aspect of ToM, involves the understanding of affective mental states. This ability is critical in the developmental phase of adolescence, which is often related with socio-emotional problems. Using a developmentally sensitive behavioral task in combination with functional magnetic resonance imaging, the present study investigated the neural development of affective ToM throughout adolescence. Eighteen adolescent (ages 12–14 years) and 18 young adult women (aged 19–25 years) were scanned while evaluating complex affective mental states depicted by actors in video clips. The ventromedial prefrontal cortex (vmPFC) showed significantly stronger activation in adolescents in comparison to adults in the affective ToM condition. Current results indicate that the vmPFC might be involved in the development of affective ToM processing in adolescence. PMID:23716712
The relationship between stress and Alzheimer's disease.

PubMed

Justice, Nicholas J

2018-02-01

Stress is critically involved in the development and progression of disease. From the stress of undergoing treatments to facing your own mortality, the physiological processes that stress drives have a serious detrimental effect on the ability to heal, cope and maintain a positive quality of life. This is becoming increasingly clear in the case of neurodegenerative diseases. Neurodegenerative diseases involve the devastating loss of cognitive and motor function which is stressful in itself, but can also disrupt neural circuits that mediate stress responses. Disrupting these circuits produces aberrant emotional and aggressive behavior that causes long-term care to be especially difficult. In addition, added stress drives progression of the disease and can exacerbate symptoms. In this review, I describe how neural and endocrine pathways activated by stress interact with ongoing neurodegenerative disease from both a clinical and experimental perspective.
Sustained Activity in Hierarchical Modular Neural Networks: Self-Organized Criticality and Oscillations

PubMed Central

Wang, Sheng-Jun; Hilgetag, Claus C.; Zhou, Changsong

2010-01-01

Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information processing. PMID:21852971
Imaging of neural oscillations with embedded inferential and group prevalence statistics.

PubMed

Donhauser, Peter W; Florin, Esther; Baillet, Sylvain

2018-02-01

Magnetoencephalography and electroencephalography (MEG, EEG) are essential techniques for studying distributed signal dynamics in the human brain. In particular, the functional role of neural oscillations remains to be clarified. For that reason, imaging methods need to identify distinct brain regions that concurrently generate oscillatory activity, with adequate separation in space and time. Yet, spatial smearing and inhomogeneous signal-to-noise are challenging factors to source reconstruction from external sensor data. The detection of weak sources in the presence of stronger regional activity nearby is a typical complication of MEG/EEG source imaging. We propose a novel, hypothesis-driven source reconstruction approach to address these methodological challenges. The imaging with embedded statistics (iES) method is a subspace scanning technique that constrains the mapping problem to the actual experimental design. A major benefit is that, regardless of signal strength, the contributions from all oscillatory sources, which activity is consistent with the tested hypothesis, are equalized in the statistical maps produced. We present extensive evaluations of iES on group MEG data, for mapping 1) induced oscillations using experimental contrasts, 2) ongoing narrow-band oscillations in the resting-state, 3) co-modulation of brain-wide oscillatory power with a seed region, and 4) co-modulation of oscillatory power with peripheral signals (pupil dilation). Along the way, we demonstrate several advantages of iES over standard source imaging approaches. These include the detection of oscillatory coupling without rejection of zero-phase coupling, and detection of ongoing oscillations in deeper brain regions, where signal-to-noise conditions are unfavorable. We also show that iES provides a separate evaluation of oscillatory synchronization and desynchronization in experimental contrasts, which has important statistical advantages. The flexibility of iES allows it to be adjusted to many experimental questions in systems neuroscience.
Imaging of neural oscillations with embedded inferential and group prevalence statistics

PubMed Central

2018-01-01

Magnetoencephalography and electroencephalography (MEG, EEG) are essential techniques for studying distributed signal dynamics in the human brain. In particular, the functional role of neural oscillations remains to be clarified. For that reason, imaging methods need to identify distinct brain regions that concurrently generate oscillatory activity, with adequate separation in space and time. Yet, spatial smearing and inhomogeneous signal-to-noise are challenging factors to source reconstruction from external sensor data. The detection of weak sources in the presence of stronger regional activity nearby is a typical complication of MEG/EEG source imaging. We propose a novel, hypothesis-driven source reconstruction approach to address these methodological challenges. The imaging with embedded statistics (iES) method is a subspace scanning technique that constrains the mapping problem to the actual experimental design. A major benefit is that, regardless of signal strength, the contributions from all oscillatory sources, which activity is consistent with the tested hypothesis, are equalized in the statistical maps produced. We present extensive evaluations of iES on group MEG data, for mapping 1) induced oscillations using experimental contrasts, 2) ongoing narrow-band oscillations in the resting-state, 3) co-modulation of brain-wide oscillatory power with a seed region, and 4) co-modulation of oscillatory power with peripheral signals (pupil dilation). Along the way, we demonstrate several advantages of iES over standard source imaging approaches. These include the detection of oscillatory coupling without rejection of zero-phase coupling, and detection of ongoing oscillations in deeper brain regions, where signal-to-noise conditions are unfavorable. We also show that iES provides a separate evaluation of oscillatory synchronization and desynchronization in experimental contrasts, which has important statistical advantages. The flexibility of iES allows it to be adjusted to many experimental questions in systems neuroscience. PMID:29408902
Integrated Cancer Research in Five Thematic Areas in Interest

DTIC Science & Technology

2005-07-01

Professor of Urology (on-going RSU), Howard Crawford, PhD, Assistant Professor of Pharmacological Sciences (on-going RSU), Marjana Maletic- Savatic ...young scientists. Drs. Adler, Crawford, Maletic- Savatic received base support from this mechanism as they further develop their research programs...Mirjana Maletic- Savatic , MD-PhD, Assistant Professor Neurology: Human Neural Stem Cells - In Vivo Models for Cerebral Carcinoma The study of human
General visual robot controller networks via artificial evolution

NASA Astrophysics Data System (ADS)

Cliff, David; Harvey, Inman; Husbands, Philip

1993-08-01

We discuss recent results from our ongoing research concerning the application of artificial evolution techniques (i.e., an extended form of genetic algorithm) to the problem of developing `neural' network controllers for visually guided robots. The robot is a small autonomous vehicle with extremely low-resolution vision, employing visual sensors which could readily be constructed from discrete analog components. In addition to visual sensing, the robot is equipped with a small number of mechanical tactile sensors. Activity from the sensors is fed to a recurrent dynamical artificial `neural' network, which acts as the robot controller, providing signals to motors governing the robot's motion. Prior to presentation of new results, this paper summarizes our rationale and past work, which has demonstrated that visually guided control networks can arise without any explicit specification that visual processing should be employed: the evolutionary process opportunistically makes use of visual information if it is available.
CFHR1-Modified Neural Stem Cells Ameliorated Brain Injury in a Mouse Model of Neuromyelitis Optica Spectrum Disorders.

PubMed

Shi, Kaibin; Wang, Zhen; Liu, Yuanchu; Gong, Ye; Fu, Ying; Li, Shaowu; Wood, Kristofer; Hao, Junwei; Zhang, Guang-Xian; Shi, Fu-Dong; Yan, Yaping

2016-11-01

A major hurdle for effective stem cell therapy is ongoing inflammation in the target organ. Reconditioning the lesion microenvironment may be an effective way to promote stem cell therapy. In this study, we showed that engineered neural stem cells (NSCs) with complement factor H-related protein 1, a complement inhibitor protein, can attenuate inflammatory infiltration and immune-mediated damage of astrocytes, an important pathogenic progress in patients with neuromyelitis optica spectrum disorders. Furthermore, we demonstrated that transplantation of the complement factor H-related protein 1-modified NSCs effectively blocked the complement activation cascade and inhibited formation of the membrane attack complex, thus contributing to the protection of endogenous and transplanted NSC-differentiated astrocytes. Therefore, manipulation of the lesion microenvironment contributes to a more effective cell replacement therapeutic strategy for autoimmune diseases of the CNS. Copyright © 2016 by The American Association of Immunologists, Inc.
Ongoing neural development of affective theory of mind in adolescence.

PubMed

Vetter, Nora C; Weigelt, Sarah; Döhnel, Katrin; Smolka, Michael N; Kliegel, Matthias

2014-07-01

Affective Theory of Mind (ToM), an important aspect of ToM, involves the understanding of affective mental states. This ability is critical in the developmental phase of adolescence, which is often related with socio-emotional problems. Using a developmentally sensitive behavioral task in combination with functional magnetic resonance imaging, the present study investigated the neural development of affective ToM throughout adolescence. Eighteen adolescent (ages 12-14 years) and 18 young adult women (aged 19-25 years) were scanned while evaluating complex affective mental states depicted by actors in video clips. The ventromedial prefrontal cortex (vmPFC) showed significantly stronger activation in adolescents in comparison to adults in the affective ToM condition. Current results indicate that the vmPFC might be involved in the development of affective ToM processing in adolescence. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
Subcortical processing of speech regularities underlies reading and music aptitude in children

PubMed Central

2011-01-01

Background Neural sensitivity to acoustic regularities supports fundamental human behaviors such as hearing in noise and reading. Although the failure to encode acoustic regularities in ongoing speech has been associated with language and literacy deficits, how auditory expertise, such as the expertise that is associated with musical skill, relates to the brainstem processing of speech regularities is unknown. An association between musical skill and neural sensitivity to acoustic regularities would not be surprising given the importance of repetition and regularity in music. Here, we aimed to define relationships between the subcortical processing of speech regularities, music aptitude, and reading abilities in children with and without reading impairment. We hypothesized that, in combination with auditory cognitive abilities, neural sensitivity to regularities in ongoing speech provides a common biological mechanism underlying the development of music and reading abilities. Methods We assessed auditory working memory and attention, music aptitude, reading ability, and neural sensitivity to acoustic regularities in 42 school-aged children with a wide range of reading ability. Neural sensitivity to acoustic regularities was assessed by recording brainstem responses to the same speech sound presented in predictable and variable speech streams. Results Through correlation analyses and structural equation modeling, we reveal that music aptitude and literacy both relate to the extent of subcortical adaptation to regularities in ongoing speech as well as with auditory working memory and attention. Relationships between music and speech processing are specifically driven by performance on a musical rhythm task, underscoring the importance of rhythmic regularity for both language and music. Conclusions These data indicate common brain mechanisms underlying reading and music abilities that relate to how the nervous system responds to regularities in auditory input. Definition of common biological underpinnings for music and reading supports the usefulness of music for promoting child literacy, with the potential to improve reading remediation. PMID:22005291
A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation.

PubMed

Fiebig, Florian; Lansner, Anders

2017-01-04

A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism. Working memory (WM) is a key component of cognition. Hypotheses about the neural mechanism behind WM are currently under revision. Reflecting recent findings of fast Hebbian synaptic plasticity in cortex, we test whether a cortical spiking neural network model with such a mechanism can learn a multi-item WM task (word list learning). We show that our model can reproduce human cognitive phenomena and achieve comparable memory performance in both free and cued recall while being simultaneously compatible with experimental data on structure, connectivity, and neurophysiology of the underlying cortical tissue. These findings are directly relevant to the ongoing paradigm shift in the WM field. Copyright © 2017 Fiebig and Lansner.
A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation

PubMed Central

Fiebig, Florian

2017-01-01

A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism. SIGNIFICANCE STATEMENT Working memory (WM) is a key component of cognition. Hypotheses about the neural mechanism behind WM are currently under revision. Reflecting recent findings of fast Hebbian synaptic plasticity in cortex, we test whether a cortical spiking neural network model with such a mechanism can learn a multi-item WM task (word list learning). We show that our model can reproduce human cognitive phenomena and achieve comparable memory performance in both free and cued recall while being simultaneously compatible with experimental data on structure, connectivity, and neurophysiology of the underlying cortical tissue. These findings are directly relevant to the ongoing paradigm shift in the WM field. PMID:28053032
Will big data yield new mathematics? An evolving synergy with neuroscience

PubMed Central

Feng, S.; Holmes, P.

2016-01-01

New mathematics has often been inspired by new insights into the natural world. Here we describe some ongoing and possible future interactions among the massive data sets being collected in neuroscience, methods for their analysis and mathematical models of the underlying, still largely uncharted neural substrates that generate these data. We start by recalling events that occurred in turbulence modelling when substantial space-time velocity field measurements and numerical simulations allowed a new perspective on the governing equations of fluid mechanics. While no analogous global mathematical model of neural processes exists, we argue that big data may enable validation or at least rejection of models at cellular to brain area scales and may illuminate connections among models. We give examples of such models and survey some relatively new experimental technologies, including optogenetics and functional imaging, that can report neural activity in live animals performing complex tasks. The search for analytical techniques for these data is already yielding new mathematics, and we believe their multi-scale nature may help relate well-established models, such as the Hodgkin–Huxley equations for single neurons, to more abstract models of neural circuits, brain areas and larger networks within the brain. In brief, we envisage a closer liaison, if not a marriage, between neuroscience and mathematics. PMID:27516705
Will big data yield new mathematics? An evolving synergy with neuroscience.

PubMed

Feng, S; Holmes, P

2016-06-01

New mathematics has often been inspired by new insights into the natural world. Here we describe some ongoing and possible future interactions among the massive data sets being collected in neuroscience, methods for their analysis and mathematical models of the underlying, still largely uncharted neural substrates that generate these data. We start by recalling events that occurred in turbulence modelling when substantial space-time velocity field measurements and numerical simulations allowed a new perspective on the governing equations of fluid mechanics. While no analogous global mathematical model of neural processes exists, we argue that big data may enable validation or at least rejection of models at cellular to brain area scales and may illuminate connections among models. We give examples of such models and survey some relatively new experimental technologies, including optogenetics and functional imaging, that can report neural activity in live animals performing complex tasks. The search for analytical techniques for these data is already yielding new mathematics, and we believe their multi-scale nature may help relate well-established models, such as the Hodgkin-Huxley equations for single neurons, to more abstract models of neural circuits, brain areas and larger networks within the brain. In brief, we envisage a closer liaison, if not a marriage, between neuroscience and mathematics.
Neural network connectivity differences in children who stutter

PubMed Central

Zhu, David C.

2013-01-01

Affecting 1% of the general population, stuttering impairs the normally effortless process of speech production, which requires precise coordination of sequential movement occurring among the articulatory, respiratory, and resonance systems, all within millisecond time scales. Those afflicted experience frequent disfluencies during ongoing speech, often leading to negative psychosocial consequences. The aetiology of stuttering remains unclear; compared to other neurodevelopmental disorders, few studies to date have examined the neural bases of childhood stuttering. Here we report, for the first time, results from functional (resting state functional magnetic resonance imaging) and structural connectivity analyses (probabilistic tractography) of multimodal neuroimaging data examining neural networks in children who stutter. We examined how synchronized brain activity occurring among brain areas associated with speech production, and white matter tracts that interconnect them, differ in young children who stutter (aged 3–9 years) compared with age-matched peers. Results showed that children who stutter have attenuated connectivity in neural networks that support timing of self-paced movement control. The results suggest that auditory-motor and basal ganglia-thalamocortical networks develop differently in stuttering children, which may in turn affect speech planning and execution processes needed to achieve fluent speech motor control. These results provide important initial evidence of neurological differences in the early phases of symptom onset in children who stutter. PMID:24131593
Rhythms of Consciousness: Binocular Rivalry Reveals Large-Scale Oscillatory Network Dynamics Mediating Visual Perception

PubMed Central

Doesburg, Sam M.; Green, Jessica J.; McDonald, John J.; Ward, Lawrence M.

2009-01-01

Consciousness has been proposed to emerge from functionally integrated large-scale ensembles of gamma-synchronous neural populations that form and dissolve at a frequency in the theta band. We propose that discrete moments of perceptual experience are implemented by transient gamma-band synchronization of relevant cortical regions, and that disintegration and reintegration of these assemblies is time-locked to ongoing theta oscillations. In support of this hypothesis we provide evidence that (1) perceptual switching during binocular rivalry is time-locked to gamma-band synchronizations which recur at a theta rate, indicating that the onset of new conscious percepts coincides with the emergence of a new gamma-synchronous assembly that is locked to an ongoing theta rhythm; (2) localization of the generators of these gamma rhythms reveals recurrent prefrontal and parietal sources; (3) theta modulation of gamma-band synchronization is observed between and within the activated brain regions. These results suggest that ongoing theta-modulated-gamma mechanisms periodically reintegrate a large-scale prefrontal-parietal network critical for perceptual experience. Moreover, activation and network inclusion of inferior temporal cortex and motor cortex uniquely occurs on the cycle immediately preceding responses signaling perceptual switching. This suggests that the essential prefrontal-parietal oscillatory network is expanded to include additional cortical regions relevant to tasks and perceptions furnishing consciousness at that moment, in this case image processing and response initiation, and that these activations occur within a time frame consistent with the notion that conscious processes directly affect behaviour. PMID:19582165
Design strategies for dynamic closed-loop optogenetic neurocontrol in vivo

NASA Astrophysics Data System (ADS)

Bolus, M. F.; Willats, A. A.; Whitmire, C. J.; Rozell, C. J.; Stanley, G. B.

2018-04-01

Objective. Controlling neural activity enables the possibility of manipulating sensory perception, cognitive processes, and body movement, in addition to providing a powerful framework for functionally disentangling the neural circuits that underlie these complex phenomena. Over the last decade, optogenetic stimulation has become an increasingly important and powerful tool for understanding neural circuit function, owing to the ability to target specific cell types and bidirectionally modulate neural activity. To date, most stimulation has been provided in open-loop or in an on/off closed-loop fashion, where previously-determined stimulation is triggered by an event. Here, we describe and demonstrate a design approach for precise optogenetic control of neuronal firing rate modulation using feedback to guide stimulation continuously. Approach. Using the rodent somatosensory thalamus as an experimental testbed for realizing desired time-varying patterns of firing rate modulation, we utilized a moving average exponential filter to estimate firing rate online from single-unit spiking measured extracellularly. This estimate of instantaneous rate served as feedback for a proportional integral (PI) controller, which was designed during the experiment based on a linear-nonlinear Poisson (LNP) model of the neuronal response to light. Main results. The LNP model fit during the experiment enabled robust closed-loop control, resulting in good tracking of sinusoidal and non-sinusoidal targets, and rejection of unmeasured disturbances. Closed-loop control also enabled manipulation of trial-to-trial variability. Significance. Because neuroscientists are faced with the challenge of dissecting the functions of circuit components, the ability to maintain control of a region of interest in spite of changes in ongoing neural activity will be important for disambiguating function within networks. Closed-loop stimulation strategies are ideal for control that is robust to such changes, and the employment of continuous feedback to adjust stimulation in real-time can improve the quality of data collected using optogenetic manipulation.
Recent advances in the pathophysiology of arterial hypertension: potential implications for clinical practice.

PubMed

Hering, Dagmara; Trzebski, Andrzej; Narkiewicz, Krzysztof

2017-03-01

Hypertension remains a major and growing public health problem associated with the greatest global rate of cardiovascular morbidity and mortality. Although numerous factors contribute to poor control of blood pressure (BP) and to pseudoresistance (eg, unawareness, lifestyle habits, nonadherence to medication, insufficient treatment, drug‑induced hypertension, undiagnosed secondary causes), true resistant hypertension (RH) is reported in 10.1% of patients treated for elevated BP. While the mechanisms underlying RH remain complex and not entirely understood, sympathetic activation involved in the pathophysiology of hypertension, disease progression, and adverse complications is further augmented in patients with drug‑resistant hypertension. The well‑established contribution of neurogenic component of hypertension has led to the introduction of new alternative therapies aimed specifically at modulating central and neural reflexes mechanisms involved in BP control. Although clinical benefits of lowering BP with renal denervation, baroreflex activation therapy, carotid body denervation, central arteriovenous anastomosis, and deep brain stimulation have advanced our knowledge on uncontrolled hypertension, the variable BP response has prompted extensive ongoing research to define predictors of treatment effectiveness and further investigation of pathophysiology of RH. Very recently, research on the role of vasopressinergic neurons, masked tachycardia, and impaired brain neural activity has provided novel insights into hypertension. This review briefly summarizes the role of the centrally mediated sympathetic nervous system in hypertension, the therapeutic strategies that distinctively target impaired neural reflex mechanisms, and potential implications for future clinical research and therapies.
Prestimulus EEG Power Predicts Conscious Awareness But Not Objective Visual Performance

PubMed Central

Veniero, Domenica

2017-01-01

Abstract Prestimulus oscillatory neural activity has been linked to perceptual outcomes during performance of psychophysical detection and discrimination tasks. Specifically, the power and phase of low frequency oscillations have been found to predict whether an upcoming weak visual target will be detected or not. However, the mechanisms by which baseline oscillatory activity influences perception remain unclear. Recent studies suggest that the frequently reported negative relationship between α power and stimulus detection may be explained by changes in detection criterion (i.e., increased target present responses regardless of whether the target was present/absent) driven by the state of neural excitability, rather than changes in visual sensitivity (i.e., more veridical percepts). Here, we recorded EEG while human participants performed a luminance discrimination task on perithreshold stimuli in combination with single-trial ratings of perceptual awareness. Our aim was to investigate whether the power and/or phase of prestimulus oscillatory activity predict discrimination accuracy and/or perceptual awareness on a trial-by-trial basis. Prestimulus power (3–28 Hz) was inversely related to perceptual awareness ratings (i.e., higher ratings in states of low prestimulus power/high excitability) but did not predict discrimination accuracy. In contrast, prestimulus oscillatory phase did not predict awareness ratings or accuracy in any frequency band. These results provide evidence that prestimulus α power influences the level of subjective awareness of threshold visual stimuli but does not influence visual sensitivity when a decision has to be made regarding stimulus features. Hence, we find a clear dissociation between the influence of ongoing neural activity on conscious awareness and objective performance. PMID:29255794
Decreased spinal synaptic inputs to phrenic motor neurons elicit localized inactivity-induced phrenic motor facilitation

PubMed Central

Streeter, K.A.; Baker-Herman, T.L.

2014-01-01

Phrenic motor neurons receive rhythmic synaptic inputs throughout life. Since even brief disruption in phrenic neural activity is detrimental to life, on-going neural activity may play a key role in shaping phrenic motor output. To test the hypothesis that spinal mechanisms sense and respond to reduced phrenic activity, anesthetized, ventilated rats received micro-injections of procaine in the C2 ventrolateral funiculus (VLF) to transiently (~30 min) block axon conduction in bulbospinal axons from medullary respiratory neurons that innervate one phrenic motor pool; during procaine injections, contralateral phrenic neural activity was maintained. Once axon conduction resumed, a prolonged increase in phrenic burst amplitude was observed in the ipsilateral phrenic nerve, demonstrating inactivity-induced phrenic motor facilitation (iPMF). Inhibition of tumor necrosis factor alpha (TNFα) and atypical PKC (aPKC) activity in spinal segments containing the phrenic motor nucleus impaired ipsilateral iPMF, suggesting a key role for spinal TNFα and aPKC in iPMF following unilateral axon conduction block. A small phrenic burst amplitude facilitation was also observed contralateral to axon conduction block, indicating crossed spinal phrenic motor facilitation (csPMF). csPMF was independent of spinal TNFα and aPKC. Ipsilateral iPMF and csPMF following unilateral withdrawal of phrenic synaptic inputs were associated with proportional increases in phrenic responses to chemoreceptor stimulation (hypercapnia), suggesting iPMF and csPMF increase phrenic dynamic range. These data suggest that local, spinal mechanisms sense and respond to reduced synaptic inputs to phrenic motor neurons. We hypothesize that iPMF and csPMF may represent compensatory mechanisms that assure adequate motor output is maintained in a physiological system in which prolonged inactivity ends life. PMID:24681155

Neural Correlates of Three Promising Endophenotypes of Depression: Evidence from the EMBARC Study

PubMed Central

Webb, Christian A; Dillon, Daniel G; Pechtel, Pia; Goer, Franziska K; Murray, Laura; Huys, Quentin JM; Fava, Maurizio; McGrath, Patrick J; Weissman, Myrna; Parsey, Ramin; Kurian, Benji T; Adams, Phillip; Weyandt, Sarah; Trombello, Joseph M; Grannemann, Bruce; Cooper, Crystal M; Deldin, Patricia; Tenke, Craig; Trivedi, Madhukar; Bruder, Gerard; Pizzagalli, Diego A

2016-01-01

Major depressive disorder (MDD) is clinically, and likely pathophysiologically, heterogeneous. A potentially fruitful approach to parsing this heterogeneity is to focus on promising endophenotypes. Guided by the NIMH Research Domain Criteria initiative, we used source localization of scalp-recorded EEG resting data to examine the neural correlates of three emerging endophenotypes of depression: neuroticism, blunted reward learning, and cognitive control deficits. Data were drawn from the ongoing multi-site EMBARC study. We estimated intracranial current density for standard EEG frequency bands in 82 unmedicated adults with MDD, using Low-Resolution Brain Electromagnetic Tomography. Region-of-interest and whole-brain analyses tested associations between resting state EEG current density and endophenotypes of interest. Neuroticism was associated with increased resting gamma (36.5–44 Hz) current density in the ventral (subgenual) anterior cingulate cortex (ACC) and orbitofrontal cortex (OFC). In contrast, reduced cognitive control correlated with decreased gamma activity in the left dorsolateral prefrontal cortex (dlPFC), decreased theta (6.5–8 Hz) and alpha2 (10.5–12 Hz) activity in the dorsal ACC, and increased alpha2 activity in the right dlPFC. Finally, blunted reward learning correlated with lower OFC and left dlPFC gamma activity. Computational modeling of trial-by-trial reinforcement learning further indicated that lower OFC gamma activity was linked to reduced reward sensitivity. Three putative endophenotypes of depression were found to have partially dissociable resting intracranial EEG correlates, reflecting different underlying neural dysfunctions. Overall, these findings highlight the need to parse the heterogeneity of MDD by focusing on promising endophenotypes linked to specific pathophysiological abnormalities. PMID:26068725
Contributions to muscle force and EMG by combined neural excitation and electrical stimulation

NASA Astrophysics Data System (ADS)

Crago, Patrick E.; Makowski, Nathaniel S.; Cole, Natalie M.

2014-10-01

Objective. Stimulation of muscle for research or clinical interventions is often superimposed on ongoing physiological activity without a quantitative understanding of the impact of the stimulation on the net muscle activity and the physiological response. Experimental studies show that total force during stimulation is less than the sum of the isolated voluntary and stimulated forces, but the occlusion mechanism is not understood. Approach. We develop a model of efferent motor activity elicited by superimposing stimulation during a physiologically activated contraction. The model combines action potential interactions due to collision block, source resetting, and refractory periods with previously published models of physiological motor unit recruitment, rate modulation, force production, and EMG generation in human first dorsal interosseous muscle to investigate the mechanisms and effectiveness of stimulation on the net muscle force and EMG. Main results. Stimulation during a physiological contraction demonstrates partial occlusion of force and the neural component of the EMG, due to action potential interactions in motor units activated by both sources. Depending on neural and stimulation firing rates as well as on force-frequency properties, individual motor unit forces can be greater, smaller, or unchanged by the stimulation. In contrast, voluntary motor unit EMG potentials in simultaneously stimulated motor units show progressive occlusion with increasing stimulus rate. The simulations predict that occlusion would be decreased by a reverse stimulation recruitment order. Significance. The results are consistent with and provide a mechanistic interpretation of previously published experimental evidence of force occlusion. The models also predict two effects that have not been reported previously—voluntary EMG occlusion and the advantages of a proximal stimulation site. This study provides a basis for the rational design of both future experiments and clinical neuroprosthetic interventions involving either motor or sensory stimulation.
Contributions to muscle force and EMG by combined neural excitation and electrical stimulation

PubMed Central

Crago, Patrick E; Makowski, Nathaniel S; Cole, Natalie M

2014-01-01

Objective Stimulation of muscle for research or clinical interventions is often superimposed on ongoing physiological activity, without a quantitative understanding of the impact of the stimulation on the net muscle activity and the physiological response. Experimental studies show that total force during stimulation is less than the sum of the isolated voluntary and stimulated forces, but the occlusion mechanism is not understood. Approach We develop a model of efferent motor activity elicited by superimposing stimulation during a physiologically activated contraction. The model combines action potential interactions due to collision block, source resetting, and refractory periods with previously published models of physiological motor unit recruitment, rate modulation, force production, and EMG generation in human first dorsal interosseous muscle to investigate the mechanisms and effectiveness of stimulation on the net muscle force and EMG. Main Results Stimulation during a physiological contraction demonstrates partial occlusion of force and the neural component of the EMG, due to action potential interactions in motor units activated by both sources. Depending on neural and stimulation firing rates as well as on force-frequency properties, individual motor unit forces can be greater, smaller, or unchanged by the stimulation. In contrast, voluntary motor unit EMG potentials in simultaneously stimulated motor units show progressive occlusion with increasing stimulus rate. The simulations predict that occlusion would be decreased by a reverse stimulation recruitment order. Significance The results are consistent with and provide a mechanistic interpretation of previously published experimental evidence of force occlusion. The models also predict two effects that have not been reported previously - voluntary EMG occlusion and the advantages of a proximal stimulation site. This study provides a basis for the rational design of both future experiments and clinical neuroprosthetic interventions involving either motor or sensory stimulation. PMID:25242203
The Impact of Anxiety-Inducing Distraction on Cognitive Performance: A Combined Brain Imaging and Personality Investigation

PubMed Central

Denkova, Ekaterina; Wong, Gloria; Dolcos, Sanda; Sung, Keen; Wang, Lihong; Coupland, Nicholas; Dolcos, Florin

2010-01-01

Background Previous investigations revealed that the impact of task-irrelevant emotional distraction on ongoing goal-oriented cognitive processing is linked to opposite patterns of activation in emotional and perceptual vs. cognitive control/executive brain regions. However, little is known about the role of individual variations in these responses. The present study investigated the effect of trait anxiety on the neural responses mediating the impact of transient anxiety-inducing task-irrelevant distraction on cognitive performance, and on the neural correlates of coping with such distraction. We investigated whether activity in the brain regions sensitive to emotional distraction would show dissociable patterns of co-variation with measures indexing individual variations in trait anxiety and cognitive performance. Methodology/Principal Findings Event-related fMRI data, recorded while healthy female participants performed a delayed-response working memory (WM) task with distraction, were investigated in conjunction with behavioural measures that assessed individual variations in both trait anxiety and WM performance. Consistent with increased sensitivity to emotional cues in high anxiety, specific perceptual areas (fusiform gyrus - FG) exhibited increased activity that was positively correlated with trait anxiety and negatively correlated with WM performance, whereas specific executive regions (right lateral prefrontal cortex - PFC) exhibited decreased activity that was negatively correlated with trait anxiety. The study also identified a role of the medial and left lateral PFC in coping with distraction, as opposed to reflecting a detrimental impact of emotional distraction. Conclusions These findings provide initial evidence concerning the neural mechanisms sensitive to individual variations in trait anxiety and WM performance, which dissociate the detrimental impact of emotion distraction and the engagement of mechanisms to cope with distracting emotions. Our study sheds light on the neural correlates of emotion-cognition interactions in normal behaviour, which has implications for understanding factors that may influence susceptibility to affective disorders, in general, and to anxiety disorders, in particular. PMID:21152391
Multiple Component Event-Related Potential (mcERP) Estimation

NASA Technical Reports Server (NTRS)

Knuth, K. H.; Clanton, S. T.; Shah, A. S.; Truccolo, W. A.; Ding, M.; Bressler, S. L.; Trejo, L. J.; Schroeder, C. E.; Clancy, Daniel (Technical Monitor)

2002-01-01

We show how model-based estimation of the neural sources responsible for transient neuroelectric signals can be improved by the analysis of single trial data. Previously, we showed that a multiple component event-related potential (mcERP) algorithm can extract the responses of individual sources from recordings of a mixture of multiple, possibly interacting, neural ensembles. McERP also estimated single-trial amplitudes and onset latencies, thus allowing more accurate estimation of ongoing neural activity during an experimental trial. The mcERP algorithm is related to informax independent component analysis (ICA); however, the underlying signal model is more physiologically realistic in that a component is modeled as a stereotypic waveshape varying both in amplitude and onset latency from trial to trial. The result is a model that reflects quantities of interest to the neuroscientist. Here we demonstrate that the mcERP algorithm provides more accurate results than more traditional methods such as factor analysis and the more recent ICA. Whereas factor analysis assumes the sources are orthogonal and ICA assumes the sources are statistically independent, the mcERP algorithm makes no such assumptions thus allowing investigators to examine interactions among components by estimating the properties of single-trial responses.
Monetary favors and their influence on neural responses and revealed preference

PubMed Central

Harvey, Ann H.; Kirk, Ulrich; Denfield, George H.; Montague, P. Read

2010-01-01

Favors from a sender to a receiver are known to bias decisions made by the recipient, especially when the decision relates to the sender – a feature of social exchange known as reciprocity. Using an art-viewing paradigm possessing no objectively correct answer for preferring one piece of art over another, we show that sponsorship of the experiment by a company endows the company’s logo with the capacity to bias revealed preference for art displayed next to the logo. Merely offering to sponsor the experiment similarly endowed the gesturing company’s logo with the capacity to bias revealed preferences. These effects do not depend upon the size of the displayed art or the proximity of the sponsoring logo to the piece of art. We used fMRI to show that such monetary favors do not modulate a special collection of brain responses, but instead modulate responses in neural networks normally activated by a wide range of preference judgments. The results raise the important possibility that monetary favors bias judgments in domains seemingly unrelated to the favor, but nevertheless act in an implicit way through neural networks that underlie normal, ongoing preference judgments. PMID:20631188
The role of alpha-rhythm states in perceptual learning: insights from experiments and computational models

PubMed Central

Sigala, Rodrigo; Haufe, Sebastian; Roy, Dipanjan; Dinse, Hubert R.; Ritter, Petra

2014-01-01

During the past two decades growing evidence indicates that brain oscillations in the alpha band (~10 Hz) not only reflect an “idle” state of cortical activity, but also take a more active role in the generation of complex cognitive functions. A recent study shows that more than 60% of the observed inter-subject variability in perceptual learning can be ascribed to ongoing alpha activity. This evidence indicates a significant role of alpha oscillations for perceptual learning and hence motivates to explore the potential underlying mechanisms. Hence, it is the purpose of this review to highlight existent evidence that ascribes intrinsic alpha oscillations a role in shaping our ability to learn. In the review, we disentangle the alpha rhythm into different neural signatures that control information processing within individual functional building blocks of perceptual learning. We further highlight computational studies that shed light on potential mechanisms regarding how alpha oscillations may modulate information transfer and connectivity changes relevant for learning. To enable testing of those model based hypotheses, we emphasize the need for multidisciplinary approaches combining assessment of behavior and multi-scale neuronal activity, active modulation of ongoing brain states and computational modeling to reveal the mathematical principles of the complex neuronal interactions. In particular we highlight the relevance of multi-scale modeling frameworks such as the one currently being developed by “The Virtual Brain” project. PMID:24772077
Measuring neural and behavioral activity during ongoing computerized social interactions: an examination of event-related brain potentials.

PubMed

Themanson, Jason R

2014-11-15

Social exclusion is a complex social phenomenon with powerful negative consequences. Given the impact of social exclusion on mental and emotional health, an understanding of how perceptions of social exclusion develop over the course of a social interaction is important for advancing treatments aimed at lessening the harmful costs of being excluded. To date, most scientific examinations of social exclusion have looked at exclusion after a social interaction has been completed. While this has been very helpful in developing an understanding of what happens to a person following exclusion, it has not helped to clarify the moment-to-moment dynamics of the process of social exclusion. Accordingly, the current protocol was developed to obtain an improved understanding of social exclusion by examining the patterns of event-related brain activation that are present during social interactions. This protocol allows greater precision and sensitivity in detailing the social processes that lead people to feel as though they have been excluded from a social interaction. Importantly, the current protocol can be adapted to include research projects that vary the nature of exclusionary social interactions by altering how frequently participants are included, how long the periods of exclusion will last in each interaction, and when exclusion will take place during the social interactions. Further, the current protocol can be used to examine variables and constructs beyond those related to social exclusion. This capability to address a variety of applications across psychology by obtaining both neural and behavioral data during ongoing social interactions suggests the present protocol could be at the core of a developing area of scientific inquiry related to social interactions.
Neural network tracking and extension of positive tracking periods

NASA Technical Reports Server (NTRS)

Hanan, Jay C.; Chao, Tien-Hsin; Moreels, Pierre

2004-01-01

Feature detectors have been considered for the role of supplying additional information to a neural network tracker. The feature detector focuses on areas of the image with significant information. Basically, if a picture says a thousand words, the feature detectors are looking for the key phrases (keypoints). These keypoints are rotationally invariant and may be matched across frames. Application of these advanced feature detectors to the neural network tracking system at JPL has promising potential. As part of an ongoing program, an advanced feature detector was tested for augmentation of a neural network based tracker. The advance feature detector extended tracking periods in test sequences including aircraft tracking, rover tracking, and simulated Martian landing. Future directions of research are also discussed.
Neural network tracking and extension of positive tracking periods

NASA Astrophysics Data System (ADS)

Hanan, Jay C.; Chao, Tien-Hsin; Moreels, Pierre

2004-04-01

Feature detectors have been considered for the role of supplying additional information to a neural network tracker. The feature detector focuses on areas of the image with significant information. Basically, if a picture says a thousand words, the feature detectors are looking for the key phrases (keypoints). These keypoints are rotationally invariant and may be matched across frames. Application of these advanced feature detectors to the neural network tracking system at JPL has promising potential. As part of an ongoing program, an advanced feature detector was tested for augmentation of a neural network based tracker. The advance feature detector extended tracking periods in test sequences including aircraft tracking, rover tracking, and simulated Martian landing. Future directions of research are also discussed.
Neural oscillatory deficits in schizophrenia predict behavioral and neurocognitive impairments

PubMed Central

Martínez, Antígona; Gaspar, Pablo A.; Hillyard, Steven A.; Bickel, Stephan; Lakatos, Peter; Dias, Elisa C.; Javitt, Daniel C.

2015-01-01

Paying attention to visual stimuli is typically accompanied by event-related desynchronizations (ERD) of ongoing alpha (7–14 Hz) activity in visual cortex. The present study used time-frequency based analyses to investigate the role of impaired alpha ERD in visual processing deficits in schizophrenia (Sz). Subjects viewed sinusoidal gratings of high (HSF) and low (LSF) spatial frequency (SF) designed to test functioning of the parvo- vs. magnocellular pathways, respectively. Patients with Sz and healthy controls paid attention selectively to either the LSF or HSF gratings which were presented in random order. Event-related brain potentials (ERPs) were recorded to all stimuli. As in our previous study, it was found that Sz patients were selectively impaired at detecting LSF target stimuli and that ERP amplitudes to LSF stimuli were diminished, both for the early sensory-evoked components and for the attend minus unattend difference component (the Selection Negativity), which is generally regarded as a specific index of feature-selective attention. In the time-frequency domain, the differential ERP deficits to LSF stimuli were echoed in a virtually absent theta-band phase locked response to both unattended and attended LSF stimuli (along with relatively intact theta-band activity for HSF stimuli). In contrast to the theta-band evoked responses which were tightly stimulus locked, stimulus-induced desynchronizations of ongoing alpha activity were not tightly stimulus locked and were apparent only in induced power analyses. Sz patients were significantly impaired in the attention-related modulation of ongoing alpha activity for both HSF and LSF stimuli. These deficits correlated with patients’ behavioral deficits in visual information processing as well as with visually based neurocognitive deficits. These findings suggest an additional, pathway-independent, mechanism by which deficits in early visual processing contribute to overall cognitive impairment in Sz. PMID:26190988
A cross-modal investigation of the neural substrates for ongoing cognition

PubMed Central

Wang, Megan; He, Biyu J.

2014-01-01

What neural mechanisms underlie the seamless flow of our waking consciousness? A necessary albeit insufficient condition for such neural mechanisms is that they should be consistently modulated across time were a segment of the conscious stream to be repeated twice. In this study, we experimentally manipulated the content of a story followed by subjects during functional magnetic resonance imaging (fMRI) independently from the modality of sensory input (as visual text or auditory speech) as well as attentional focus. We then extracted brain activity patterns consistently modulated across subjects by the evolving content of the story regardless of whether it was presented visually or auditorily. Specifically, in one experiment we presented the same story to different subjects via either auditory or visual modality. In a second experiment, we presented two different stories simultaneously, one auditorily, one visually, and manipulated the subjects' attentional focus. This experimental design allowed us to dissociate brain activities underlying modality-specific sensory processing from modality-independent story processing. We uncovered a network of brain regions consistently modulated by the evolving content of a story regardless of the sensory modality used for stimulus input, including the superior temporal sulcus/gyrus (STS/STG), the inferior frontal gyrus (IFG), the posterior cingulate cortex (PCC), the medial frontal cortex (MFC), the temporal pole (TP), and the temporoparietal junction (TPJ). Many of these regions have previously been implicated in semantic processing. Interestingly, different stories elicited similar brain activity patterns, but with subtle differences potentially attributable to varying degrees of emotional valence and self-relevance. PMID:25206347
Remembering forward: Neural correlates of memory and prediction in human motor adaptation

PubMed Central

Scheidt, Robert A; Zimbelman, Janice L; Salowitz, Nicole M G; Suminski, Aaron J; Mosier, Kristine M; Houk, James; Simo, Lucia

2011-01-01

We used functional MR imaging (FMRI), a robotic manipulandum and systems identification techniques to examine neural correlates of predictive compensation for spring-like loads during goal-directed wrist movements in neurologically-intact humans. Although load changed unpredictably from one trial to the next, subjects nevertheless used sensorimotor memories from recent movements to predict and compensate upcoming loads. Prediction enabled subjects to adapt performance so that the task was accomplished with minimum effort. Population analyses of functional images revealed a distributed, bilateral network of cortical and subcortical activity supporting predictive load compensation during visual target capture. Cortical regions - including prefrontal, parietal and hippocampal cortices - exhibited trial-by-trial fluctuations in BOLD signal consistent with the storage and recall of sensorimotor memories or “states” important for spatial working memory. Bilateral activations in associative regions of the striatum demonstrated temporal correlation with the magnitude of kinematic performance error (a signal that could drive reward-optimizing reinforcement learning and the prospective scaling of previously learned motor programs). BOLD signal correlations with load prediction were observed in the cerebellar cortex and red nuclei (consistent with the idea that these structures generate adaptive fusimotor signals facilitating cancellation of expected proprioceptive feedback, as required for conditional feedback adjustments to ongoing motor commands and feedback error learning). Analysis of single subject images revealed that predictive activity was at least as likely to be observed in more than one of these neural systems as in just one. We conclude therefore that motor adaptation is mediated by predictive compensations supported by multiple, distributed, cortical and subcortical structures. PMID:21840405
A method for closed-loop presentation of sensory stimuli conditional on the internal brain-state of awake animals

PubMed Central

Rutishauser, Ueli; Kotowicz, Andreas; Laurent, Gilles

2013-01-01

Brain activity often consists of interactions between internal—or on-going—and external—or sensory—activity streams, resulting in complex, distributed patterns of neural activity. Investigation of such interactions could benefit from closed-loop experimental protocols in which one stream can be controlled depending on the state of the other. We describe here methods to present rapid and precisely timed visual stimuli to awake animals, conditional on features of the animal’s on-going brain state; those features are the presence, power and phase of oscillations in local field potentials (LFP). The system can process up to 64 channels in real time. We quantified its performance using simulations, synthetic data and animal experiments (chronic recordings in the dorsal cortex of awake turtles). The delay from detection of an oscillation to the onset of a visual stimulus on an LCD screen was 47.5 ms and visual-stimulus onset could be locked to the phase of ongoing oscillations at any frequency ≤40 Hz. Our software’s architecture is flexible, allowing on-the-fly modifications by experimenters and the addition of new closed-loop control and analysis components through plugins. The source code of our system “StimOMatic” is available freely as open-source. PMID:23473800
Motor Behavior Activates Bergmann Glial Networks

PubMed Central

Nimmerjahn, Axel; Mukamel, Eran A.; Schnitzer, Mark J.

2010-01-01

SUMMARY Although it is firmly established neuronal activity is a prime determinant of animal behavior, relationships between astrocytic excitation and animal behavior have remained opaque. Cerebellar Bergmann glia are radial astrocytes that are implicated in motor behavior and exhibit Ca2+-excitation. However, Ca2+-excitation in these cells has not previously been studied in behaving animals. Using two-photon microscopy we found that Bergmann glia exhibit three forms of Ca2+-excitation in awake behaving mice. Two of these are ongoing within the cerebellar vermis. During locomotor performance concerted Ca2+-excitation arises in networks of at least hundreds of Bergmann glia extending across several hundred microns or more. Concerted Ca2+-excitation was abolished by anesthesia or blockade of either neural activity or glutamatergic transmission. Thus, large networks of Bergmann glia can be activated by specific animal behaviors and undergo excitation of sufficient magnitude to potentially initiate macroscopic changes in brain dynamics or blood flow. PMID:19447095
Cross-modal orienting of visual attention.

PubMed

Hillyard, Steven A; Störmer, Viola S; Feng, Wenfeng; Martinez, Antigona; McDonald, John J

2016-03-01

This article reviews a series of experiments that combined behavioral and electrophysiological recording techniques to explore the hypothesis that salient sounds attract attention automatically and facilitate the processing of visual stimuli at the sound's location. This cross-modal capture of visual attention was found to occur even when the attracting sound was irrelevant to the ongoing task and was non-predictive of subsequent events. A slow positive component in the event-related potential (ERP) that was localized to the visual cortex was found to be closely coupled with the orienting of visual attention to a sound's location. This neural sign of visual cortex activation was predictive of enhanced perceptual processing and was paralleled by a desynchronization (blocking) of the ongoing occipital alpha rhythm. Further research is needed to determine the nature of the relationship between the slow positive ERP evoked by the sound and the alpha desynchronization and to understand how these electrophysiological processes contribute to improved visual-perceptual processing. Copyright © 2015 Elsevier Ltd. All rights reserved.
Toward a model-based cognitive neuroscience of mind wandering.

PubMed

Hawkins, G E; Mittner, M; Boekel, W; Heathcote, A; Forstmann, B U

2015-12-03

People often "mind wander" during everyday tasks, temporarily losing track of time, place, or current task goals. In laboratory-based tasks, mind wandering is often associated with performance decrements in behavioral variables and changes in neural recordings. Such empirical associations provide descriptive accounts of mind wandering - how it affects ongoing task performance - but fail to provide true explanatory accounts - why it affects task performance. In this perspectives paper, we consider mind wandering as a neural state or process that affects the parameters of quantitative cognitive process models, which in turn affect observed behavioral performance. Our approach thus uses cognitive process models to bridge the explanatory divide between neural and behavioral data. We provide an overview of two general frameworks for developing a model-based cognitive neuroscience of mind wandering. The first approach uses neural data to segment observed performance into a discrete mixture of latent task-related and task-unrelated states, and the second regresses single-trial measures of neural activity onto structured trial-by-trial variation in the parameters of cognitive process models. We discuss the relative merits of the two approaches, and the research questions they can answer, and highlight that both approaches allow neural data to provide additional constraint on the parameters of cognitive models, which will lead to a more precise account of the effect of mind wandering on brain and behavior. We conclude by summarizing prospects for mind wandering as conceived within a model-based cognitive neuroscience framework, highlighting the opportunities for its continued study and the benefits that arise from using well-developed quantitative techniques to study abstract theoretical constructs. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Tracking Deceased-Related Thinking with Neural Pattern Decoding of a Cortical-Basal Ganglia Circuit.

PubMed

Schneck, Noam; Haufe, Stefan; Tu, Tao; Bonanno, George A; Ochsner, Kevin; Sajda, Paul; Mann, J John

2017-07-01

Deceased-related thinking is central to grieving and potentially critical to processing of the loss. Self-report measurements might fail to capture important elements of deceased-related thinking and processing. Here, we used a machine learning approach applied to fMRI - known as neural decoding - to develop a measure of ongoing deceased-related processing. 23 subjects grieving the loss of a first-degree relative, spouse or partner within 14 months underwent two fMRI tasks. They first viewed pictures and stories related to the deceased, a living control and a demographic control figure while providing ongoing valence and arousal ratings. Second, they performed a 10-minute Sustained Attention to Response Task (SART) with thought probes every 25-35 seconds to identify deceased, living and self-related thoughts. A conjunction analysis, controlling for valence/arousal, identified neural clusters in basal ganglia, orbital prefrontal cortex and insula associated with both types of deceased-related stimuli vs. the two control conditions in the first task. This pattern was applied to fMRI data collected during the SART, and discriminated deceased-related but not living or self-related thoughts, independently of grief-severity and time since loss. Deceased-related thoughts on the SART correlated with self-reported avoidance. The neural model predicted avoidance over and above deceased-related thoughts. A neural pattern trained to identify mental representations of the deceased tracked deceased-related thinking during a sustained attention task and also predicted subject-level avoidance. This approach provides a new imaging tool to be used as an index of processing the deceased for future studies of complicated grief.
Neuropsychology of aging, past, present and future: Contributions of Morris Moscovitch.

PubMed

Reuter-Lorenz, Patricia A; Cooke, Katherine A

2016-09-01

In this review we provide a broad overview of major trends in the cognitive neuroscience of aging and illustrate their roots in the pioneering ideas and discoveries of Morris Moscovitch and his close collaborators, especially Gordon Winocur. These trends include an on-going focus on the specific and dissociable contributions of medial temporal and frontal lobe processes to cognitive aging, especially in the memory domain, the role of individual variability stemming from different patterns of underlying neural decline, the possibility of compensatory neural and cognitive influences that alter the expression of neurobiological aging, and the investigation of lifestyle and psychosocial factors that affect plasticity and may contribute to the rate and level of neurocognitive decline. These prescient ideas, evident in the early work of Moscovitch and Winocur, continue to drive on-going research efforts in the cognitive neuroscience of aging. Copyright © 2016 Elsevier Ltd. All rights reserved.
Circles of Engagement: Childhood Pain and Parent Brain

PubMed Central

Simons, Laura; Goubert, Liesbet; Vervoort, Tine; Borsook, David

2016-01-01

Social interaction can have a profound effect on individual behavior, perhaps most salient in interactions between sick suffering children and their parents. Chronic pain is a difficult condition that can produce considerable changes in behaviors in children that can secondarily have profound effects on their parents. It may create a functionally disabling negative feedback loop. Research supports the notion of alterations in the brain of individuals who observe and empathize with loved ones in acute pain. However, neural activity in relation to empathic responses in the context of chronic pain has not been examined. Ongoing suffering with chronic pain in a child can result in child's brain circuit alterations. However, prolonged suffering jointly experienced by the parent may putatively also produce maladaptive changes in their neural networks and consequently in parental behaviors. Here we put forth the conceptual framework for ‘Chronic pain contagion’ (CPC). We review the underlying processes in CPC and we discuss implications for devising and implementing treatments for children in chronic pain and their parents. PMID:27320958

Cajal and the Conceptual Weakness of Neural Sciences

PubMed Central

Delgado-García, José M.

2015-01-01

The experimental and conceptual contributions of Santiago Ramón y Cajal remain almost as fresh and valuable as when his original proposals were published more than a century ago—a rare example, contrasting with other related sciences. His basic concepts on the neuron as the main building block of the central nervous system, the dynamic polarization principle as a way to understand how neurons deal with ongoing active processes, and brain local structural arrangements as a result of the functional specialization of selected neural circuits are concepts still surviving in present research papers dealing with brain function during the performance of cognitive and/or behavioral activities. What is more, the central dogma of the Neuroscience of today, i.e., brain plasticity as the morpho-functional substrate of memory and learning processes, was already proposed and documented with notable insights by Ramón y Cajal. From this background, I will try to discuss in this chapter which new functional and structural concepts have been introduced in contemporary Neuroscience and how we will be able to construct a set of basic principles underlying brain functions for the twenty-first century. PMID:26483644
Cortex-wide BOLD fMRI activity reflects locally-recorded slow oscillation-associated calcium waves.

PubMed

Schwalm, Miriam; Schmid, Florian; Wachsmuth, Lydia; Backhaus, Hendrik; Kronfeld, Andrea; Aedo Jury, Felipe; Prouvot, Pierre-Hugues; Fois, Consuelo; Albers, Franziska; van Alst, Timo; Faber, Cornelius; Stroh, Albrecht

2017-09-15

Spontaneous slow oscillation-associated slow wave activity represents an internally generated state which is characterized by alternations of network quiescence and stereotypical episodes of neuronal activity - slow wave events. However, it remains unclear which macroscopic signal is related to these active periods of the slow wave rhythm. We used optic fiber-based calcium recordings of local neural populations in cortex and thalamus to detect neurophysiologically defined slow calcium waves in isoflurane anesthetized rats. The individual slow wave events were used for an event-related analysis of simultaneously acquired whole-brain BOLD fMRI. We identified BOLD responses directly related to onsets of slow calcium waves, revealing a cortex-wide BOLD correlate: the entire cortex was engaged in this specific type of slow wave activity. These findings demonstrate a direct relation of defined neurophysiological events to a specific BOLD activity pattern and were confirmed for ongoing slow wave activity by independent component and seed-based analyses.
Cortex-wide BOLD fMRI activity reflects locally-recorded slow oscillation-associated calcium waves

PubMed Central

Backhaus, Hendrik; Kronfeld, Andrea; Aedo Jury, Felipe; Prouvot, Pierre-Hugues; Fois, Consuelo; Albers, Franziska; van Alst, Timo

2017-01-01

Spontaneous slow oscillation-associated slow wave activity represents an internally generated state which is characterized by alternations of network quiescence and stereotypical episodes of neuronal activity - slow wave events. However, it remains unclear which macroscopic signal is related to these active periods of the slow wave rhythm. We used optic fiber-based calcium recordings of local neural populations in cortex and thalamus to detect neurophysiologically defined slow calcium waves in isoflurane anesthetized rats. The individual slow wave events were used for an event-related analysis of simultaneously acquired whole-brain BOLD fMRI. We identified BOLD responses directly related to onsets of slow calcium waves, revealing a cortex-wide BOLD correlate: the entire cortex was engaged in this specific type of slow wave activity. These findings demonstrate a direct relation of defined neurophysiological events to a specific BOLD activity pattern and were confirmed for ongoing slow wave activity by independent component and seed-based analyses. PMID:28914607
Adaptation to a cortex controlled robot attached at the pelvis and engaged during locomotion in rats

PubMed Central

Song, Weiguo; Giszter, Simon F.

2011-01-01

Brain Machine Interfaces (BMIs) should ideally show robust adaptation of the BMI across different tasks and daily activities. Most BMIs have used over-practiced tasks. Little is known about BMIs in dynamic environments. How are mechanically body-coupled BMIs integrated into ongoing rhythmic dynamics, e.g., in locomotion? To examine this we designed a novel BMI using neural discharge in the hindlimb/trunk motor cortex in rats during locomotion to control a robot attached at the pelvis. We tested neural adaptation when rats experienced (a) control locomotion, (b) ‘simple elastic load’ (a robot load on locomotion without any BMI neural control) and (c) ‘BMI with elastic load’ (in which the robot loaded locomotion and a BMI neural control could counter this load). Rats significantly offset applied loads with the BMI while preserving more normal pelvic height compared to load alone. Adaptation occurred over about 100–200 step cycles in a trial. Firing rates increased in both the loaded conditions compared to baseline. Mean phases of cells’ discharge in the step cycle shifted significantly between BMI and the simple load condition. Over time more BMI cells became positively correlated with the external force and modulated more deeply, and neurons’ network correlations on a 100ms timescale increased. Loading alone showed none of these effects. The BMI neural changes of rate and force correlations persisted or increased over repeated trials. Our results show that rats have the capacity to use motor adaptation and motor learning to fairly rapidly engage hindlimb/trunk coupled BMIs in their locomotion. PMID:21414932
Differential polarization of cortical pyramidal neuron dendrites through weak extracellular fields

PubMed Central

Obermayer, Klaus

2018-01-01

The rise of transcranial current stimulation (tCS) techniques have sparked an increasing interest in the effects of weak extracellular electric fields on neural activity. These fields modulate ongoing neural activity through polarization of the neuronal membrane. While the somatic polarization has been investigated experimentally, the frequency-dependent polarization of the dendritic trees in the presence of alternating (AC) fields has received little attention yet. Using a biophysically detailed model with experimentally constrained active conductances, we analyze the subthreshold response of cortical pyramidal cells to weak AC fields, as induced during tCS. We observe a strong frequency resonance around 10-20 Hz in the apical dendrites sensitivity to polarize in response to electric fields but not in the basal dendrites nor the soma. To disentangle the relative roles of the cell morphology and active and passive membrane properties in this resonance, we perform a thorough analysis using simplified models, e.g. a passive pyramidal neuron model, simple passive cables and reconstructed cell model with simplified ion channels. We attribute the origin of the resonance in the apical dendrites to (i) a locally increased sensitivity due to the morphology and to (ii) the high density of h-type channels. Our systematic study provides an improved understanding of the subthreshold response of cortical cells to weak electric fields and, importantly, allows for an improved design of tCS stimuli. PMID:29727454
Brain State Is a Major Factor in Preseizure Hippocampal Network Activity and Influences Success of Seizure Intervention

PubMed Central

Ewell, Laura A.; Liang, Liang; Armstrong, Caren; Soltész, Ivan; Leutgeb, Stefan

2015-01-01

Neural dynamics preceding seizures are of interest because they may shed light on mechanisms of seizure generation and could be predictive. In healthy animals, hippocampal network activity is shaped by behavioral brain state and, in epilepsy, seizures selectively emerge during specific brain states. To determine the degree to which changes in network dynamics before seizure are pathological or reflect ongoing fluctuations in brain state, dorsal hippocampal neurons were recorded during spontaneous seizures in a rat model of temporal lobe epilepsy. Seizures emerged from all brain states, but with a greater likelihood after REM sleep, potentially due to an observed increase in baseline excitability during periods of REM compared with other brains states also characterized by sustained theta oscillations. When comparing the firing patterns of the same neurons across brain states associated with and without seizures, activity dynamics before seizures followed patterns typical of the ongoing brain state, or brain state transitions, and did not differ until the onset of the electrographic seizure. Next, we tested whether disparate activity patterns during distinct brain states would influence the effectiveness of optogenetic curtailment of hippocampal seizures in a mouse model of temporal lobe epilepsy. Optogenetic curtailment was significantly more effective for seizures preceded by non-theta states compared with seizures that emerged from theta states. Our results indicate that consideration of behavioral brain state preceding a seizure is important for the appropriate interpretation of network dynamics leading up to a seizure and for designing effective seizure intervention. SIGNIFICANCE STATEMENT Hippocampal single-unit activity is strongly shaped by behavioral brain state, yet this relationship has been largely ignored when studying activity dynamics before spontaneous seizures in medial temporal lobe epilepsy. In light of the increased attention on using single-unit activity for the prediction of seizure onset and closed-loop seizure intervention, we show a need for monitoring brain state to interpret correctly whether changes in neural activity before seizure onset is pathological or normal. Moreover, we also find that the brain state preceding a seizure determines the success of therapeutic interventions to curtail seizure duration. Together, these findings suggest that seizure prediction and intervention will be more successful if tailored for the specific brain states from which seizures emerge. PMID:26609157
M-type potassium conductance controls the emergence of neural phase codes: a combined experimental and neuron modelling study

PubMed Central

Kwag, Jeehyun; Jang, Hyun Jae; Kim, Mincheol; Lee, Sujeong

2014-01-01

Rate and phase codes are believed to be important in neural information processing. Hippocampal place cells provide a good example where both coding schemes coexist during spatial information processing. Spike rate increases in the place field, whereas spike phase precesses relative to the ongoing theta oscillation. However, what intrinsic mechanism allows for a single neuron to generate spike output patterns that contain both neural codes is unknown. Using dynamic clamp, we simulate an in vivo-like subthreshold dynamics of place cells to in vitro CA1 pyramidal neurons to establish an in vitro model of spike phase precession. Using this in vitro model, we show that membrane potential oscillation (MPO) dynamics is important in the emergence of spike phase codes: blocking the slowly activating, non-inactivating K+ current (IM), which is known to control subthreshold MPO, disrupts MPO and abolishes spike phase precession. We verify the importance of adaptive IM in the generation of phase codes using both an adaptive integrate-and-fire and a Hodgkin–Huxley (HH) neuron model. Especially, using the HH model, we further show that it is the perisomatically located IM with slow activation kinetics that is crucial for the generation of phase codes. These results suggest an important functional role of IM in single neuron computation, where IM serves as an intrinsic mechanism allowing for dual rate and phase coding in single neurons. PMID:25100320
Neural substrates underlying the tendency to accept anger-infused ultimatum offers during dynamic social interactions.

PubMed

Gilam, Gadi; Lin, Tamar; Raz, Gal; Azrielant, Shir; Fruchter, Eyal; Ariely, Dan; Hendler, Talma

2015-10-15

In managing our way through interpersonal conflict, anger might be crucial in determining whether the dispute escalates to aggressive behaviors or resolves cooperatively. The Ultimatum Game (UG) is a social decision-making paradigm that provides a framework for studying interpersonal conflict over division of monetary resources. Unfair monetary UG-offers elicit anger and while accepting them engages regulatory processes, rejecting them is regarded as an aggressive retribution. Ventro-medial prefrontal-cortex (vmPFC) activity has been shown to relate to idiosyncratic tendencies in accepting unfair offers possibly through its role in emotion regulation. Nevertheless, standard UG paradigms lack fundamental aspects of real-life social interactions in which one reacts to other people in a response contingent fashion. To uncover the neural substrates underlying the tendency to accept anger-infused ultimatum offers during dynamic social interactions, we incorporated on-line verbal negotiations with an obnoxious partner in a repeated-UG during fMRI scanning. We hypothesized that vmPFC activity will differentiate between individuals with high or low monetary gains accumulated throughout the game and reflect a divergence in the associated emotional experience. We found that as individuals gained more money, they reported less anger but also more positive feelings and had slower sympathetic response. In addition, high-gain individuals had increased vmPFC activity, but also decreased brainstem activity, which possibly reflected the locus coeruleus. During the more angering unfair offers, these individuals had increased dorsal-posterior Insula (dpI) activity which functionally coupled to the medial-thalamus (mT). Finally, both vmPFC activity and dpI-mT connectivity contributed to increased gain, possibly by modulating the ongoing subjective emotional experience. These ecologically valid findings point towards a neural mechanism that might nurture pro-social interactions by modulating an individual's dynamic emotional experience. Copyright © 2015 Elsevier Inc. All rights reserved.
On the design of script languages for neural simulation.

PubMed

Brette, Romain

2012-01-01

In neural network simulators, models are specified according to a language, either specific or based on a general programming language (e.g. Python). There are also ongoing efforts to develop standardized languages, for example NeuroML. When designing these languages, efforts are often focused on expressivity, that is, on maximizing the number of model types than can be described and simulated. I argue that a complementary goal should be to minimize the cognitive effort required on the part of the user to use the language. I try to formalize this notion with the concept of "language entropy", and I propose a few practical guidelines to minimize the entropy of languages for neural simulation.
Neural signal processing and closed-loop control algorithm design for an implanted neural recording and stimulation system.

PubMed

Hamilton, Lei; McConley, Marc; Angermueller, Kai; Goldberg, David; Corba, Massimiliano; Kim, Louis; Moran, James; Parks, Philip D; Sang Chin; Widge, Alik S; Dougherty, Darin D; Eskandar, Emad N

2015-08-01

A fully autonomous intracranial device is built to continually record neural activities in different parts of the brain, process these sampled signals, decode features that correlate to behaviors and neuropsychiatric states, and use these features to deliver brain stimulation in a closed-loop fashion. In this paper, we describe the sampling and stimulation aspects of such a device. We first describe the signal processing algorithms of two unsupervised spike sorting methods. Next, we describe the LFP time-frequency analysis and feature derivation from the two spike sorting methods. Spike sorting includes a novel approach to constructing a dictionary learning algorithm in a Compressed Sensing (CS) framework. We present a joint prediction scheme to determine the class of neural spikes in the dictionary learning framework; and, the second approach is a modified OSort algorithm which is implemented in a distributed system optimized for power efficiency. Furthermore, sorted spikes and time-frequency analysis of LFP signals can be used to generate derived features (including cross-frequency coupling, spike-field coupling). We then show how these derived features can be used in the design and development of novel decode and closed-loop control algorithms that are optimized to apply deep brain stimulation based on a patient's neuropsychiatric state. For the control algorithm, we define the state vector as representative of a patient's impulsivity, avoidance, inhibition, etc. Controller parameters are optimized to apply stimulation based on the state vector's current state as well as its historical values. The overall algorithm and software design for our implantable neural recording and stimulation system uses an innovative, adaptable, and reprogrammable architecture that enables advancement of the state-of-the-art in closed-loop neural control while also meeting the challenges of system power constraints and concurrent development with ongoing scientific research designed to define brain network connectivity and neural network dynamics that vary at the individual patient level and vary over time.
Complementary fMRI and EEG evidence for more efficient neural processing of rhythmic vs. unpredictably timed sounds

PubMed Central

van Atteveldt, Nienke; Musacchia, Gabriella; Zion-Golumbic, Elana; Sehatpour, Pejman; Javitt, Daniel C.; Schroeder, Charles

2015-01-01

The brain’s fascinating ability to adapt its internal neural dynamics to the temporal structure of the sensory environment is becoming increasingly clear. It is thought to be metabolically beneficial to align ongoing oscillatory activity to the relevant inputs in a predictable stream, so that they will enter at optimal processing phases of the spontaneously occurring rhythmic excitability fluctuations. However, some contexts have a more predictable temporal structure than others. Here, we tested the hypothesis that the processing of rhythmic sounds is more efficient than the processing of irregularly timed sounds. To do this, we simultaneously measured functional magnetic resonance imaging (fMRI) and electro-encephalograms (EEG) while participants detected oddball target sounds in alternating blocks of rhythmic (e.g., with equal inter-stimulus intervals) or random (e.g., with randomly varied inter-stimulus intervals) tone sequences. Behaviorally, participants detected target sounds faster and more accurately when embedded in rhythmic streams. The fMRI response in the auditory cortex was stronger during random compared to random tone sequence processing. Simultaneously recorded N1 responses showed larger peak amplitudes and longer latencies for tones in the random (vs. the rhythmic) streams. These results reveal complementary evidence for more efficient neural and perceptual processing during temporally predictable sensory contexts. PMID:26579044
Neural Conflict–Control Mechanisms Improve Memory for Target Stimuli

PubMed Central

Krebs, Ruth M.; Boehler, Carsten N.; De Belder, Maya; Egner, Tobias

2015-01-01

According to conflict-monitoring models, conflict serves as an internal signal for reinforcing top-down attention to task-relevant information. While evidence based on measures of ongoing task performance supports this idea, implications for long-term consequences, that is, memory, have not been tested yet. Here, we evaluated the prediction that conflict-triggered attentional enhancement of target-stimulus processing should be associated with superior subsequent memory for those stimuli. By combining functional magnetic resonance imaging (fMRI) with a novel variant of a face-word Stroop task that employed trial-unique face stimuli as targets, we were able to assess subsequent (incidental) memory for target faces as a function of whether a given face had previously been accompanied by congruent, neutral, or incongruent (conflicting) distracters. In line with our predictions, incongruent distracters not only induced behavioral conflict, but also gave rise to enhanced memory for target faces. Moreover, conflict-triggered neural activity in prefrontal and parietal regions was predictive of subsequent retrieval success, and displayed conflict-enhanced functional coupling with medial-temporal lobe regions. These data provide support for the proposal that conflict evokes enhanced top-down attention to task-relevant stimuli, thereby promoting their encoding into long-term memory. Our findings thus delineate the neural mechanisms of a novel link between cognitive control and memory. PMID:24108799
Short-term field stimulation mimics synaptic maturation of hippocampal synapses

PubMed Central

Bagley, Elena E; Westbrook, Gary L

2012-01-01

Many aspects of synaptic transmission are modified during development, reflecting not only the consequence of developmental programmes of gene expression, but also the effects of ongoing neural activity. We investigated the role of synaptic activity in the maturation of Schaffer collateral (SC)–CA1 synapses using sustained low frequency field stimulation of acute brain slices. Between postnatal days 4–6 and 14–16, mouse SC–CA1 synapses in naïve slices showed a developmental decrease in the probability of transmitter release (Pr) and an increase in the contribution of GluN2A (NR2A) subunits to the NMDA receptor-mediated excitatory postsynaptic current (EPSC). Surprisingly, these developmental changes could be mimicked by short term (4 h) in vitro synaptic activity in slices taken from postnatal days (PND) 4–6 mice. However, different activity levels were required to alter release probability compared to the NMDA receptor subunit composition. Spontaneous synaptic activity was sufficient to alter the NMDA receptor subunit composition, but sustained low-frequency field stimulation of the brain slice (0.1 Hz, 4 h) was necessary to reduce release probability, as assessed 1 h following the cessation of stimulation. The protein synthesis inhibitor anisomycin blocked the effect of field stimulation on release probability. These results indicate that features of mature excitatory synapses can be rapidly induced in immature neurons. The activity dependence of the Pr and NMDA receptor subunit composition serves as a sensitive indicator of prior neural activity, and provides dual mechanisms for homeostatic control of excitatory synaptic efficacy. PMID:22351628
Short-term field stimulation mimics synaptic maturation of hippocampal synapses.

PubMed

Bagley, Elena E; Westbrook, Gary L

2012-04-01

Many aspects of synaptic transmission are modified during development, reflecting not only the consequence of developmental programmes of gene expression, but also the effects of ongoing neural activity. We investigated the role of synaptic activity in the maturation of Schaffer collateral (SC)-CA1 synapses using sustained low frequency field stimulation of acute brain slices. Between postnatal days 4-6 and 14-16, mouse SC-CA1 synapses in naïve slices showed a developmental decrease in the probability of transmitter release (P(r)) and an increase in the contribution of GluN2A (NR2A) subunits to the NMDA receptor-mediated excitatory postsynaptic current (EPSC). Surprisingly, these developmental changes could be mimicked by short term (4 h) in vitro synaptic activity in slices taken from postnatal days (PND) 4-6 mice. However, different activity levels were required to alter release probability compared to the NMDA receptor subunit composition. Spontaneous synaptic activity was sufficient to alter the NMDA receptor subunit composition, but sustained low-frequency field stimulation of the brain slice (0.1 Hz, 4 h) was necessary to reduce release probability, as assessed 1 h following the cessation of stimulation. The protein synthesis inhibitor anisomycin blocked the effect of field stimulation on release probability. These results indicate that features of mature excitatory synapses can be rapidly induced in immature neurons. The activity dependence of the P(r) and NMDA receptor subunit composition serves as a sensitive indicator of prior neural activity, and provides dual mechanisms for homeostatic control of excitatory synaptic efficacy.
Why Are There Developmental Stages in Language Learning? A Developmental Robotics Model of Language Development.

PubMed

Morse, Anthony F; Cangelosi, Angelo

2017-02-01

Most theories of learning would predict a gradual acquisition and refinement of skills as learning progresses, and while some highlight exponential growth, this fails to explain why natural cognitive development typically progresses in stages. Models that do span multiple developmental stages typically have parameters to "switch" between stages. We argue that by taking an embodied view, the interaction between learning mechanisms, the resulting behavior of the agent, and the opportunities for learning that the environment provides can account for the stage-wise development of cognitive abilities. We summarize work relevant to this hypothesis and suggest two simple mechanisms that account for some developmental transitions: neural readiness focuses on changes in the neural substrate resulting from ongoing learning, and perceptual readiness focuses on the perceptual requirements for learning new tasks. Previous work has demonstrated these mechanisms in replications of a wide variety of infant language experiments, spanning multiple developmental stages. Here we piece this work together as a single model of ongoing learning with no parameter changes at all. The model, an instance of the Epigenetic Robotics Architecture (Morse et al 2010) embodied on the iCub humanoid robot, exhibits ongoing multi-stage development while learning pre-linguistic and then basic language skills. Copyright © 2016 Cognitive Science Society, Inc.
Toward Real Time Neural Net Flight Controllers

NASA Technical Reports Server (NTRS)

Jorgensen, C. C.; Mah, R. W.; Ross, J.; Lu, Henry, Jr. (Technical Monitor)

1994-01-01

NASA Ames Research Center has an ongoing program in neural network control technology targeted toward real time flight demonstrations using a modified F-15 which permits direct inner loop control of actuators, rapid switching between alternative control designs, and substitutable processors. An important part of this program is the ACTIVE flight project which is examining the feasibility of using neural networks in the design, control, and system identification of new aircraft prototypes. This paper discusses two research applications initiated with this objective in mind: utilization of neural networks for wind tunnel aircraft model identification and rapid learning algorithms for on line reconfiguration and control. The first application involves the identification of aerodynamic flight characteristics from analysis of wind tunnel test data. This identification is important in the early stages of aircraft design because complete specification of control architecture's may not be possible even though concept models at varying scales are available for aerodynamic wind tunnel testing. Testing of this type is often a long and expensive process involving measurement of aircraft lift, drag, and moment of inertia at varying angles of attack and control surface configurations. This information in turn can be used in the design of the flight control systems by applying the derived lookup tables to generate piece wise linearized controllers. Thus, reduced costs in tunnel test times and the rapid transfer of wind tunnel insights into prototype controllers becomes an important factor in more efficient generation and testing of new flight systems. NASA Ames Research Center is successfully applying modular neural networks as one way of anticipating small scale aircraft model performances prior to testing, thus reducing the number of in tunnel test hours and potentially, the number of intermediate scaled models required for estimation of surface flow effects.
Detection of an inhibitory cortical gradient underlying peak shift in learning: a neural basis for a false memory.

PubMed

Miasnikov, Alexandre A; Weinberger, Norman M

2012-11-01

Experience often does not produce veridical memory. Understanding false attribution of events constitutes an important problem in memory research. "Peak shift" is a well-characterized, controllable phenomenon in which human and animal subjects that receive reinforcement associated with one sensory stimulus later respond maximally to another stimulus in post-training stimulus generalization tests. Peak shift ordinarily develops in discrimination learning (reinforced CS+, unreinforced CS-) and has long been attributed to the interaction of an excitatory gradient centered on the CS+ and an inhibitory gradient centered on the CS-; the shift is away from the CS-. In contrast, we have obtained peak shifts during single tone frequency training, using stimulation of the cholinergic nucleus basalis (NB) to implant behavioral memory into the rat. As we also recorded cortical activity, we took the opportunity to investigate the possible existence of a neural frequency gradient that could account for behavioral peak shift. Behavioral frequency generalization gradients (FGGs, interruption of ongoing respiration) were determined twice before training while evoked potentials were recorded from the primary auditory cortex (A1), to obtain a baseline gradient of "habituatory" neural decrement. A post-training behavioral FGG obtained 24h after three daily sessions of a single tone paired with NB stimulation (200 trials/day) revealed a peak shift. The peak of the FGG was at a frequency lower than the CS while the cortical inhibitory gradient was at a frequency higher than the CS frequency. Further analysis indicated that the frequency location and magnitude of the gradient could account for the behavioral peak shift. These results provide a neural basis for a systematic case of memory misattribution and may provide an animal model for the study of the neural bases of a type of "false memory". Published by Elsevier Inc.
Dynamics of corticospinal motor control during overground and treadmill walking in humans.

PubMed

Roeder, Luisa; Boonstra, Tjeerd Willem; Smith, Simon S; Kerr, Graham K

2018-05-30

Increasing evidence suggests cortical involvement in the control of human gait. However, the nature of corticospinal interactions remains poorly understood. We performed time-frequency analysis of electrophysiological activity acquired during treadmill and overground walking in 22 healthy, young adults. Participants walked at their preferred speed (4.2, SD 0.4 km h -1 ), which was matched across both gait conditions. Event-related power, corticomuscular coherence (CMC) and inter-trial coherence (ITC) were assessed for EEG from bilateral sensorimotor cortices and EMG from the bilateral tibialis anterior (TA) muscles. Cortical power, CMC and ITC at theta, alpha, beta and gamma frequencies (4-45 Hz) increased during the double support phase of the gait cycle for both overground and treadmill walking. High beta (21-30 Hz) CMC and ITC of EMG was significantly increased during overground compared to treadmill walking, as well as EEG power in theta band (4-7 Hz). The phase spectra revealed positive time lags at alpha, beta and gamma frequencies, indicating that the EEG response preceded the EMG response. The parallel increases in power, CMC and ITC during double support suggest evoked responses at spinal and cortical populations rather than a modulation of ongoing corticospinal oscillatory interactions. The evoked responses are not consistent with the idea of synchronization of ongoing corticospinal oscillations, but instead suggest coordinated cortical and spinal inputs during the double support phase. Frequency-band dependent differences in power, CMC and ITC between overground and treadmill walking suggest differing neural control for the two gait modalities, emphasizing the task-dependent nature of neural processes during human walking.
Using Brain–Computer Interfaces and Brain-State Dependent Stimulation as Tools in Cognitive Neuroscience

PubMed Central

Jensen, Ole; Bahramisharif, Ali; Oostenveld, Robert; Klanke, Stefan; Hadjipapas, Avgis; Okazaki, Yuka O.; van Gerven, Marcel A. J.

2011-01-01

Large efforts are currently being made to develop and improve online analysis of brain activity which can be used, e.g., for brain–computer interfacing (BCI). A BCI allows a subject to control a device by willfully changing his/her own brain activity. BCI therefore holds the promise as a tool for aiding the disabled and for augmenting human performance. While technical developments obviously are important, we will here argue that new insight gained from cognitive neuroscience can be used to identify signatures of neural activation which reliably can be modulated by the subject at will. This review will focus mainly on oscillatory activity in the alpha band which is strongly modulated by changes in covert attention. Besides developing BCIs for their traditional purpose, they might also be used as a research tool for cognitive neuroscience. There is currently a strong interest in how brain-state fluctuations impact cognition. These state fluctuations are partly reflected by ongoing oscillatory activity. The functional role of the brain state can be investigated by introducing stimuli in real-time to subjects depending on the actual state of the brain. This principle of brain-state dependent stimulation may also be used as a practical tool for augmenting human behavior. In conclusion, new approaches based on online analysis of ongoing brain activity are currently in rapid development. These approaches are amongst others informed by new insight gained from electroencephalography/magnetoencephalography studies in cognitive neuroscience and hold the promise of providing new ways for investigating the brain at work. PMID:21687463
Is the Brain a Quantum Computer?

ERIC Educational Resources Information Center

Litt, Abninder; Eliasmith, Chris; Kroon, Frederick W.; Weinstein, Steven; Thagard, Paul

2006-01-01

We argue that computation via quantum mechanical processes is irrelevant to explaining how brains produce thought, contrary to the ongoing speculations of many theorists. First, quantum effects do not have the temporal properties required for neural information processing. Second, there are substantial physical obstacles to any organic…

Attentional neurocomputing

NASA Astrophysics Data System (ADS)

Speidel, Steven

1992-08-01

Our ultimate goal is to develop neural-like cognitive sensory processing within non-neuronal systems. Toward this end, computational models are being developed for selectivity attending the task-relevant parts of composite sensory excitations in an example sound processing application. Significant stimuli partials are selectively attended through the use of generalized neural adaptive beamformers. Computational components are being tested by experiment in the laboratory and also by use of recordings from sensor deployments in the ocean. Results will be presented. These computational components are being integrated into a comprehensive processing architecture that simultaneously attends memory according to stimuli, attends stimuli according to memory, and attends stimuli and memory according to an ongoing thought process. The proposed neural architecture is potentially very fast when implemented in special hardware.
Effects of Nerve Injury and Segmental Regeneration on the Cellular Correlates of Neural Morphallaxis

PubMed Central

Martinez, Veronica G.; Manson, Josiah M.B.; Zoran, Mark J.

2009-01-01

Functional recovery of neural networks after injury requires a series of signaling events similar to the embryonic processes that governed initial network construction. Neural morphallaxis, a form of nervous system regeneration, involves reorganization of adult neural connectivity patterns. Neural morphallaxis in the worm, Lumbriculus variegatus, occurs during asexual reproduction and segmental regeneration, as body fragments acquire new positional identities along the anterior–posterior axis. Ectopic head (EH) formation, induced by ventral nerve cord lesion, generated morphallactic plasticity including the reorganization of interneuronal sensory fields and the induction of a molecular marker of neural morphallaxis. Morphallactic changes occurred only in segments posterior to an EH. Neither EH formation, nor neural morphallaxis was observed after dorsal body lesions, indicating a role for nerve cord injury in morphallaxis induction. Furthermore, a hierarchical system of neurobehavioral control was observed, where anterior heads were dominant and an EH controlled body movements only in the absence of the anterior head. Both suppression of segmental regeneration and blockade of asexual fission, after treatment with boric acid, disrupted the maintenance of neural morphallaxis, but did not block its induction. Therefore, segmental regeneration (i.e., epimorphosis) may not be required for the induction of morphallactic remodeling of neural networks. However, on-going epimorphosis appears necessary for the long-term consolidation of cellular and molecular mechanisms underlying the morphallaxis of neural circuitry. PMID:18561185
Time Within:. the Perceptual Rivalry Switch as a Neural Clock

NASA Astrophysics Data System (ADS)

Pettigrew, John D.; Tilden, Jan D.

2005-10-01

Attention is drawn to weaknesses in the case for an external, physical basis for time's perceptual phenomena, raising the possibility of a Darwinian evolutionary explanation for the apparent flow, structure and arrow of time. We develop the hypothesis that, of all arrows of time identified by physicists and philosophers, the most fundamental is the psychological arrow. Based on findings of an on-going program of empirical research, we suggest a neural basis for time phenomena in the rhythmicity and plasticity of one of the brainstem dopaminergic nuclei, the venetral tegmental area (VTA). We examine links between neural time-keeping and perceptual rivalry and discuss evidence that rivalry is mediated by the VTA which functions as an ultradian oscillator. Further research is suggested, which could challenge or support the hypothesis of the VTA as an important neural time-keeper and the subjective basis of the asymmetric phenomena of time.
Neural stem cell apoptosis after low-methylmercury exposures in postnatal hippocampus produce persistent cell loss and adolescent memory deficits.

PubMed

Sokolowski, Katie; Obiorah, Maryann; Robinson, Kelsey; McCandlish, Elizabeth; Buckley, Brian; DiCicco-Bloom, Emanuel

2013-12-01

The developing brain is particularly sensitive to exposures to environmental contaminants. In contrast to the adult, the developing brain contains large numbers of dividing neuronal precursors, suggesting that they may be vulnerable targets. The postnatal day 7 (P7) rat hippocampus has populations of both mature neurons in the CA1-3 region as well as neural stem cells (NSC) in the dentate gyrus (DG) hilus, which actively produce new neurons that migrate to the granule cell layer (GCL). Using this well-characterized NSC population, we examined the impact of low levels of methylmercury (MeHg) on proliferation, neurogenesis, and subsequent adolescent learning and memory behavior. Assessing a range of exposures, we found that a single subcutaneous injection of 0.6 µg/g MeHg in P7 rats induced caspase activation in proliferating NSC of the hilus and GCL. This acute NSC death had lasting impact on the DG at P21, reducing cell numbers in the hilus by 22% and the GCL by 27%, as well as reductions in neural precursor proliferation by 25%. In contrast, non-proliferative CA1-3 pyramidal neuron cell number was unchanged. Furthermore, animals exposed to P7 MeHg exhibited an adolescent spatial memory deficit as assessed by Morris water maze. These results suggest that environmentally relevant levels of MeHg exposure may decrease NSC populations and, despite ongoing neurogenesis, the brain may not restore the hippocampal cell deficits, which may contribute to hippocampal-dependent memory deficits during adolescence. Copyright © 2013 Wiley Periodicals, Inc.
Theta-frequency phase-locking of single anterior cingulate cortex neurons and synchronization with the medial thalamus are modulated by visceral noxious stimulation in rats.

PubMed

Wang, J; Cao, B; Yu, T R; Jelfs, B; Yan, J; Chan, R H M; Li, Y

2015-07-09

The rodent anterior cingulate cortex (ACC) is critical for visceral pain and pain-related aversive response in chronic visceral hypersensitive (VH) state. Long-term potentiation (LTP), induced by theta burst stimulation (TBS) in the medial thalamus (MT)-ACC pathway, is blocked in VH rats. However, the neuronal intrinsic firing characteristics and the MT-ACC connectivity have not been investigated in visceral pain. Using repetitive distension of the colon and rectum (rCRD) as a sensitization paradigm, we have identified that the spontaneous firing rates of ACC neurons and the CRD-stimulated neuronal firings were increased after repetitive visceral noxious stimulation. This correlates with increases in visceral pain responses (visceromotor responses, VMRs). Two multichannel arrays of electrodes were implanted in the MT and ACC. Recordings were performed in free-moving rats before and after repeated CRD treatment. Power spectral density analysis showed that the local field potential (LFP) recorded in the ACC displayed increases in theta band power (4-10 Hz) that were modulated by rCRD. Neural spike activity in the ACC becomes synchronized with ongoing theta oscillations of LFP. Furthermore, cross correlation analysis showed augmented synchronization of thalamo-ACC theta band LFPs, which was consistent with an increase of neuronal communication between the two regions. In conclusion, these results reveal theta oscillations and theta-frequency phase-locking as prominent features of neural activity in the ACC and a candidate neural mechanism underlying acute visceral pain. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Non-peristaltic patterns of motor activity in the guinea-pig proximal colon.

PubMed

Hennig, G W; Gregory, S; Brookes, S J H; Costa, M

2010-06-01

The guinea-pig proximal colon contains semi-solid feces which are propelled by intermittent neural peristaltic waves to the distal colon, where solid pellets are formed. Between propulsive periods, complex motor patterns underlie fluid re-absorption and mixing of contents. Spatio-temporal analysis of video recordings were used to investigate neural and myogenic patterns of non-peristaltic motor activity. At low distension (6 cmH(2)O), two major motor patterns were seen. Narrow rings of constriction (abrupt contractions) occurred at 19 cpm. These previously undescribed contractions occurred, almost simultaneously, at many points along the preparation, with a calculated propagation velocity of 110 mm s(-1). They were abolished by hexamethonium and by tetrodotoxin, indicating they were neurally mediated. Inhibition of nitric oxide synthase resulted in increased frequency of 'abrupt contractions' suggesting ongoing inhibitory modulation by endogenous nitric oxide. After tetrodotoxin, another distinct motor pattern was revealed; 'ripples'(1) consisted of shallow rings of contraction, occurring at 18 cpm and propagating at 2.7-2.9 mm s(-1) orally or aborally from multiple initiation sites. The frequency of 'ripples' increased as intraluminal pressure was raised, becoming very irregular at high distensions. L-type calcium channel blockers and openers affected the amplitude of 'ripples'. No frequency gradient of 'ripples' along the proximal colon was detected. This absence explains the multiple initiation sites which often shifted over time, and the oral and aboral propagation of 'ripples'. The interaction of myogenic 'ripples' with neurogenic 'abrupt contractions' generates localized alternating rings of contractions and dilatation, well suited to effective mixing of contents.
Optogenetic feedback control of neural activity

PubMed Central

Newman, Jonathan P; Fong, Ming-fai; Millard, Daniel C; Whitmire, Clarissa J; Stanley, Garrett B; Potter, Steve M

2015-01-01

Optogenetic techniques enable precise excitation and inhibition of firing in specified neuronal populations and artifact-free recording of firing activity. Several studies have suggested that optical stimulation provides the precision and dynamic range requisite for closed-loop neuronal control, but no approach yet permits feedback control of neuronal firing. Here we present the ‘optoclamp’, a feedback control technology that provides continuous, real-time adjustments of bidirectional optical stimulation in order to lock spiking activity at specified targets over timescales ranging from seconds to days. We demonstrate how this system can be used to decouple neuronal firing levels from ongoing changes in network excitability due to multi-hour periods of glutamatergic or GABAergic neurotransmission blockade in vitro as well as impinging vibrissal sensory drive in vivo. This technology enables continuous, precise optical control of firing in neuronal populations in order to disentangle causally related variables of circuit activation in a physiologically and ethologically relevant manner. DOI: http://dx.doi.org/10.7554/eLife.07192.001 PMID:26140329
Relationships between cortical myeloarchitecture and electrophysiological networks

PubMed Central

Hunt, Benjamin A. E.; Tewarie, Prejaas K.; Mougin, Olivier E.; Geades, Nicolas; Singh, Krish D.; Morris, Peter G.; Gowland, Penny A.; Brookes, Matthew J.

2016-01-01

The human brain relies upon the dynamic formation and dissolution of a hierarchy of functional networks to support ongoing cognition. However, how functional connectivities underlying such networks are supported by cortical microstructure remains poorly understood. Recent animal work has demonstrated that electrical activity promotes myelination. Inspired by this, we test a hypothesis that gray-matter myelin is related to electrophysiological connectivity. Using ultra-high field MRI and the principle of structural covariance, we derive a structural network showing how myelin density differs across cortical regions and how separate regions can exhibit similar myeloarchitecture. Building upon recent evidence that neural oscillations mediate connectivity, we use magnetoencephalography to elucidate networks that represent the major electrophysiological pathways of communication in the brain. Finally, we show that a significant relationship exists between our functional and structural networks; this relationship differs as a function of neural oscillatory frequency and becomes stronger when integrating oscillations over frequency bands. Our study sheds light on the way in which cortical microstructure supports functional networks. Further, it paves the way for future investigations of the gray-matter structure/function relationship and its breakdown in pathology. PMID:27830650
Therapeutic use of dextromethorphan: key learnings from treatment of pseudobulbar affect.

PubMed

Miller, Ariel; Panitch, Hillel

2007-08-15

A variety of neurological conditions and disease states are accompanied by pseudobulbar affect (PBA), an emotional disorder characterized by uncontrollable outbursts of laughing and crying. The causes of PBA are unclear but may involve lesions in neural circuits regulating the motor output of emotional expression. Several agents used in treating other psychiatric disorders have been applied in the treatment of PBA with some success but data are limited and these agents are associated with unpleasant side effects due to nonspecific activity in diffuse neural networks. Dextromethorphan (DM), a widely used cough suppressant, acts at receptors in the brainstem and cerebellum, brain regions implicated in the regulation of emotional output. The combination of DM and quinidine (Q), an enzyme inhibitor that blocks DM metabolism, has recently been tested in phase III clinical trials in patients with multiple sclerosis and amyotrophic lateral sclerosis and was both safe and effective in palliating PBA symptoms. In addition, clinical studies pertaining to the safety and efficacy of DM/Q in a variety of neurological disease states are ongoing.
A robotic approach to understanding the role and the mechanism of vicarious trial-and-error in a T-maze task.

PubMed

Matsuda, Eiko; Hubert, Julien; Ikegami, Takashi

2014-01-01

Vicarious trial-and-error (VTE) is a behavior observed in rat experiments that seems to suggest self-conflict. This behavior is seen mainly when the rats are uncertain about making a decision. The presence of VTE is regarded as an indicator of a deliberative decision-making process, that is, searching, predicting, and evaluating outcomes. This process is slower than automated decision-making processes, such as reflex or habituation, but it allows for flexible and ongoing control of behavior. In this study, we propose for the first time a robotic model of VTE to see if VTE can emerge just from a body-environment interaction and to show the underlying mechanism responsible for the observation of VTE and the advantages provided by it. We tried several robots with different parameters, and we have found that they showed three different types of VTE: high numbers of VTE at the beginning of learning, decreasing numbers afterward (similar VTE pattern to experiments with rats), low during the whole learning period, and high numbers all the time. Therefore, we were able to reproduce the phenomenon of VTE in a model robot using only a simple dynamical neural network with Hebbian learning, which suggests that VTE is an emergent property of a plastic and embodied neural network. From a comparison of the three types of VTE, we demonstrated that 1) VTE is associated with chaotic activity of neurons in our model and 2) VTE-showing robots were robust to environmental perturbations. We suggest that the instability of neuronal activity found in VTE allows ongoing learning to rebuild its strategy continuously, which creates robust behavior. Based on these results, we suggest that VTE is caused by a similar mechanism in biology and leads to robust decision making in an analogous way.
Impairment of decision making and disruption of synchrony between basolateral amygdala and anterior cingulate cortex in the maternally separated rat.

PubMed

Cao, Bing; Wang, Jun; Zhang, Xu; Yang, Xiangwei; Poon, David Chun-Hei; Jelfs, Beth; Chan, Rosa H M; Wu, Justin Che-Yuen; Li, Ying

2016-12-01

There is considerable evidence to suggest early life experiences, such as maternal separation (MS), play a role in the prevalence of emotional dysregulation and cognitive impairment. At the same time, optimal decision making requires functional integrity between the amygdala and anterior cingulate cortex (ACC), and any dysfunction of this system is believed to induce decision-making deficits. However, the impact of MS on decision-making behavior and the underlying neurophysiological mechanisms have not been thoroughly studied. As such, we consider the impact of MS on the emotional and cognitive functions of rats by employing the open-field test, elevated plus-maze test, and rat gambling task (RGT). Using multi-channel recordings from freely behaving rats, we assessed the effects of MS on the large scale synchrony between the basolateral amygdala (BLA) and the ACC; while also characterizing the relationship between neural spiking activity and the ongoing oscillations in theta frequency band across the BLA and ACC. The results indicated that the MS rats demonstrated anxiety-like behavior. While the RGT showed a decrease in the percentage of good decision-makers, and an increase in the percentage of poor decision-makers. Electrophysiological data revealed an increase in the total power in the theta band of the LFP in the BLA and a decrease in theta power in the ACC in MS rats. MS was also found to disrupt the spike-field coherence of the ACC single unit spiking activity to the ongoing theta oscillations in the BLA and interrupt the synchrony in the BLA-ACC pathway. We provide specific evidence that MS leads to decision-making deficits that are accompanied by alteration of the theta band LFP in the BLA-ACC circuitries and disruption of the neural network integrity. These observations may help revise fundamental notions regarding neurophysiological biomarkers to treat cognitive impairment induced by early life stress. Copyright Â© 2016 Elsevier Inc. All rights reserved.
Autonomous Optimization of Targeted Stimulation of Neuronal Networks

PubMed Central

Kumar, Sreedhar S.; Wülfing, Jan; Okujeni, Samora; Boedecker, Joschka; Riedmiller, Martin

2016-01-01

Driven by clinical needs and progress in neurotechnology, targeted interaction with neuronal networks is of increasing importance. Yet, the dynamics of interaction between intrinsic ongoing activity in neuronal networks and their response to stimulation is unknown. Nonetheless, electrical stimulation of the brain is increasingly explored as a therapeutic strategy and as a means to artificially inject information into neural circuits. Strategies using regular or event-triggered fixed stimuli discount the influence of ongoing neuronal activity on the stimulation outcome and are therefore not optimal to induce specific responses reliably. Yet, without suitable mechanistic models, it is hardly possible to optimize such interactions, in particular when desired response features are network-dependent and are initially unknown. In this proof-of-principle study, we present an experimental paradigm using reinforcement-learning (RL) to optimize stimulus settings autonomously and evaluate the learned control strategy using phenomenological models. We asked how to (1) capture the interaction of ongoing network activity, electrical stimulation and evoked responses in a quantifiable ‘state’ to formulate a well-posed control problem, (2) find the optimal state for stimulation, and (3) evaluate the quality of the solution found. Electrical stimulation of generic neuronal networks grown from rat cortical tissue in vitro evoked bursts of action potentials (responses). We show that the dynamic interplay of their magnitudes and the probability to be intercepted by spontaneous events defines a trade-off scenario with a network-specific unique optimal latency maximizing stimulus efficacy. An RL controller was set to find this optimum autonomously. Across networks, stimulation efficacy increased in 90% of the sessions after learning and learned latencies strongly agreed with those predicted from open-loop experiments. Our results show that autonomous techniques can exploit quantitative relationships underlying activity-response interaction in biological neuronal networks to choose optimal actions. Simple phenomenological models can be useful to validate the quality of the resulting controllers. PMID:27509295
Autonomous Optimization of Targeted Stimulation of Neuronal Networks.

PubMed

Kumar, Sreedhar S; Wülfing, Jan; Okujeni, Samora; Boedecker, Joschka; Riedmiller, Martin; Egert, Ulrich

2016-08-01

Driven by clinical needs and progress in neurotechnology, targeted interaction with neuronal networks is of increasing importance. Yet, the dynamics of interaction between intrinsic ongoing activity in neuronal networks and their response to stimulation is unknown. Nonetheless, electrical stimulation of the brain is increasingly explored as a therapeutic strategy and as a means to artificially inject information into neural circuits. Strategies using regular or event-triggered fixed stimuli discount the influence of ongoing neuronal activity on the stimulation outcome and are therefore not optimal to induce specific responses reliably. Yet, without suitable mechanistic models, it is hardly possible to optimize such interactions, in particular when desired response features are network-dependent and are initially unknown. In this proof-of-principle study, we present an experimental paradigm using reinforcement-learning (RL) to optimize stimulus settings autonomously and evaluate the learned control strategy using phenomenological models. We asked how to (1) capture the interaction of ongoing network activity, electrical stimulation and evoked responses in a quantifiable 'state' to formulate a well-posed control problem, (2) find the optimal state for stimulation, and (3) evaluate the quality of the solution found. Electrical stimulation of generic neuronal networks grown from rat cortical tissue in vitro evoked bursts of action potentials (responses). We show that the dynamic interplay of their magnitudes and the probability to be intercepted by spontaneous events defines a trade-off scenario with a network-specific unique optimal latency maximizing stimulus efficacy. An RL controller was set to find this optimum autonomously. Across networks, stimulation efficacy increased in 90% of the sessions after learning and learned latencies strongly agreed with those predicted from open-loop experiments. Our results show that autonomous techniques can exploit quantitative relationships underlying activity-response interaction in biological neuronal networks to choose optimal actions. Simple phenomenological models can be useful to validate the quality of the resulting controllers.
A preliminary study of the effects of working memory training on brain function.

PubMed

Stevens, Michael C; Gaynor, Alexandra; Bessette, Katie L; Pearlson, Godfrey D

2016-06-01

Working memory (WM) training improves WM ability in Attention-Deficit/Hyperactivity Disorder (ADHD), but its efficacy for non-cognitive ADHD impairments ADHD has been sharply debated. The purpose of this preliminary study was to characterize WM training-related changes in ADHD brain function and see if they were linked to clinical improvement. We examined 18 adolescents diagnosed with DSM-IV Combined-subtype ADHD before and after 25 sessions of WM training using a frequently employed approach (Cogmed™) using a nonverbal Sternberg WM fMRI task, neuropsychological tests, and participant- and parent-reports of ADHD symptom severity and associated functional impairment. Whole brain SPM8 analyses identified ADHD activation deficits compared to 18 non-ADHD control participants, then tested whether impaired ADHD frontoparietal brain activation would increase following WM training. Post hoc tests examined the relationships between neural changes and neurocognitive or clinical improvements. As predicted, WM training increased WM performance, ADHD clinical functioning, and WM-related ADHD brain activity in several frontal, parietal and temporal lobe regions. Increased left inferior frontal sulcus region activity was seen in all Encoding, Maintenance, and Retrieval Sternberg task phases. ADHD symptom severity improvements were most often positively correlated with activation gains in brain regions known to be engaged for WM-related executive processing; improvement of different symptom types had different neural correlates. The responsiveness of both amodal WM frontoparietal circuits and executive process-specific WM brain regions was altered by WM training. The latter might represent a promising, relatively unexplored treatment target for researchers seeking to optimize clinical response in ongoing ADHD WM training development efforts.
Biomarkers and Stimulation Algorithms for Adaptive Brain Stimulation

PubMed Central

Hoang, Kimberly B.; Cassar, Isaac R.; Grill, Warren M.; Turner, Dennis A.

2017-01-01

The goal of this review is to describe in what ways feedback or adaptive stimulation may be delivered and adjusted based on relevant biomarkers. Specific treatment mechanisms underlying therapeutic brain stimulation remain unclear, in spite of the demonstrated efficacy in a number of nervous system diseases. Brain stimulation appears to exert widespread influence over specific neural networks that are relevant to specific disease entities. In awake patients, activation or suppression of these neural networks can be assessed by either symptom alleviation (i.e., tremor, rigidity, seizures) or physiological criteria, which may be predictive of expected symptomatic treatment. Secondary verification of network activation through specific biomarkers that are linked to symptomatic disease improvement may be useful for several reasons. For example, these biomarkers could aid optimal intraoperative localization, possibly improve efficacy or efficiency (i.e., reduced power needs), and provide long-term adaptive automatic adjustment of stimulation parameters. Possible biomarkers for use in portable or implanted devices span from ongoing physiological brain activity, evoked local field potentials (LFPs), and intermittent pathological activity, to wearable devices, biochemical, blood flow, optical, or magnetic resonance imaging (MRI) changes, temperature changes, or optogenetic signals. First, however, potential biomarkers must be correlated directly with symptom or disease treatment and network activation. Although numerous biomarkers are under consideration for a variety of stimulation indications the feasibility of these approaches has yet to be fully determined. Particularly, there are critical questions whether the use of adaptive systems can improve efficacy over continuous stimulation, facilitate adjustment of stimulation interventions and improve our understanding of the role of abnormal network function in disease mechanisms. PMID:29066947
Neural conflict-control mechanisms improve memory for target stimuli.

PubMed

Krebs, Ruth M; Boehler, Carsten N; De Belder, Maya; Egner, Tobias

2015-03-01

According to conflict-monitoring models, conflict serves as an internal signal for reinforcing top-down attention to task-relevant information. While evidence based on measures of ongoing task performance supports this idea, implications for long-term consequences, that is, memory, have not been tested yet. Here, we evaluated the prediction that conflict-triggered attentional enhancement of target-stimulus processing should be associated with superior subsequent memory for those stimuli. By combining functional magnetic resonance imaging (fMRI) with a novel variant of a face-word Stroop task that employed trial-unique face stimuli as targets, we were able to assess subsequent (incidental) memory for target faces as a function of whether a given face had previously been accompanied by congruent, neutral, or incongruent (conflicting) distracters. In line with our predictions, incongruent distracters not only induced behavioral conflict, but also gave rise to enhanced memory for target faces. Moreover, conflict-triggered neural activity in prefrontal and parietal regions was predictive of subsequent retrieval success, and displayed conflict-enhanced functional coupling with medial-temporal lobe regions. These data provide support for the proposal that conflict evokes enhanced top-down attention to task-relevant stimuli, thereby promoting their encoding into long-term memory. Our findings thus delineate the neural mechanisms of a novel link between cognitive control and memory. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
A 100-Channel Hermetically Sealed Implantable Device for Chronic Wireless Neurosensing Applications

PubMed Central

Yin, Ming; Borton, David A.; Aceros, Juan; Patterson, William R.; Nurmikko, Arto V.

2014-01-01

A 100-channel fully implantable wireless broadband neural recording system was developed. It features 100 parallel broadband (0.1 Hz–7.8 kHz) neural recording channels, a medical grade 200 mAh Li-ion battery recharged inductively at 150 kHz, and data telemetry using 3.2 GHz to 3.8 GHz FSK modulated wireless link for 48 Mbps Manchester encoded data. All active electronics are hermetically sealed in a titanium enclosure with a sapphire window for electromagnetic transparency. A custom, high-density configuration of 100 individual hermetic feedthrough pins enable connection to an intracortical neural recording microelectrode array. A 100 MHz bandwidth custom receiver was built to remotely receive the FSK signal and achieved −77.7 dBm sensitivity with 10−8 BER at 48 Mbps data rate. ESD testing on all the electronic inputs and outputs has proven that the implantable device satisfies the HBM Class-1B ESD Standard. In addition, the evaluation of the worst-case charge density delivered to the tissue from each I/O pin verifies the patient safety of the device in the event of failure. Finally, the functionality and reliability of the complete device has been tested on-bench and further validated chronically in ongoing freely moving swine and monkey animal trials for more than one year to date. PMID:23853294
A modular, closed-loop platform for intracranial stimulation in people with neurological disorders.

PubMed

Sarma, Anish A; Crocker, Britni; Cash, Sydney S; Truccolo, Wilson

2016-08-01

Neuromodulation systems based on electrical stimulation can be used to investigate, probe, and potentially treat a range of neurological disorders. The effects of ongoing neural state and dynamics on stimulation response, and of stimulation parameters on neural state, have broad implications for the development of closed-loop neuro-modulation approaches. We describe the development of a modular, low-latency platform for pre-clinical, closed-loop neuromodulation studies with human participants. We illustrate the uses of the platform in a stimulation case study with a person with epilepsy undergoing neuro-monitoring prior to resective surgery. We demonstrate the efficacy of the system by tracking interictal epileptiform discharges in the local field potential to trigger intracranial electrical stimulation, and show that the response to stimulation depends on the neural state.
ShapeShop: Towards Understanding Deep Learning Representations via Interactive Experimentation.

PubMed

Hohman, Fred; Hodas, Nathan; Chau, Duen Horng

2017-05-01

Deep learning is the driving force behind many recent technologies; however, deep neural networks are often viewed as "black-boxes" due to their internal complexity that is hard to understand. Little research focuses on helping people explore and understand the relationship between a user's data and the learned representations in deep learning models. We present our ongoing work, ShapeShop, an interactive system for visualizing and understanding what semantics a neural network model has learned. Built using standard web technologies, ShapeShop allows users to experiment with and compare deep learning models to help explore the robustness of image classifiers.
Neural evidence for Reference-dependence in real-market-transactions.

PubMed

Weber, Bernd; Aholt, Andreas; Neuhaus, Carolin; Trautner, Peter; Elger, Christian E; Teichert, Thorsten

2007-03-01

Human decision making has become one of the major research-foci in economics, marketing and in neuroscience. This study integrates perspectives from these disciplines by examining neurophysiological correlates to Reference-dependence of utility evaluations in real market contexts both before and after choice. First, by comparing buying and selling decisions, we observe an activation of the amygdala only in the latter. We interpret this as loss aversion with respect to prior possessions. This finding contributes to the settling of an ongoing fundamental dispute in economic theory by indicating the absence of loss aversion for money in routine transactions. Second, ex post satisfaction statements are accompanied by an activation of the reward processing orbitofrontal cortex, if the evaluation context is framed by a high external reference price instead of a lower internal reference price. This indicates a nonrational Reference-dependence--despite the neoclassical view of a rational Homo Economicus--of satisfaction measures and challenges a central marketing variable.

Real-time camera-based face detection using a modified LAMSTAR neural network system

NASA Astrophysics Data System (ADS)

Girado, Javier I.; Sandin, Daniel J.; DeFanti, Thomas A.; Wolf, Laura K.

2003-03-01

This paper describes a cost-effective, real-time (640x480 at 30Hz) upright frontal face detector as part of an ongoing project to develop a video-based, tetherless 3D head position and orientation tracking system. The work is specifically targeted for auto-stereoscopic displays and projection-based virtual reality systems. The proposed face detector is based on a modified LAMSTAR neural network system. At the input stage, after achieving image normalization and equalization, a sub-window analyzes facial features using a neural network. The sub-window is segmented, and each part is fed to a neural network layer consisting of a Kohonen Self-Organizing Map (SOM). The output of the SOM neural networks are interconnected and related by correlation-links, and can hence determine the presence of a face with enough redundancy to provide a high detection rate. To avoid tracking multiple faces simultaneously, the system is initially trained to track only the face centered in a box superimposed on the display. The system is also rotationally and size invariant to a certain degree.
Frequency modulation entrains slow neural oscillations and optimizes human listening behavior

PubMed Central

Henry, Molly J.; Obleser, Jonas

2012-01-01

The human ability to continuously track dynamic environmental stimuli, in particular speech, is proposed to profit from “entrainment” of endogenous neural oscillations, which involves phase reorganization such that “optimal” phase comes into line with temporally expected critical events, resulting in improved processing. The current experiment goes beyond previous work in this domain by addressing two thus far unanswered questions. First, how general is neural entrainment to environmental rhythms: Can neural oscillations be entrained by temporal dynamics of ongoing rhythmic stimuli without abrupt onsets? Second, does neural entrainment optimize performance of the perceptual system: Does human auditory perception benefit from neural phase reorganization? In a human electroencephalography study, listeners detected short gaps distributed uniformly with respect to the phase angle of a 3-Hz frequency-modulated stimulus. Listeners’ ability to detect gaps in the frequency-modulated sound was not uniformly distributed in time, but clustered in certain preferred phases of the modulation. Moreover, the optimal stimulus phase was individually determined by the neural delta oscillation entrained by the stimulus. Finally, delta phase predicted behavior better than stimulus phase or the event-related potential after the gap. This study demonstrates behavioral benefits of phase realignment in response to frequency-modulated auditory stimuli, overall suggesting that frequency fluctuations in natural environmental input provide a pacing signal for endogenous neural oscillations, thereby influencing perceptual processing. PMID:23151506
Primary Auditory Cortex is Required for Anticipatory Motor Response.

PubMed

Li, Jingcheng; Liao, Xiang; Zhang, Jianxiong; Wang, Meng; Yang, Nian; Zhang, Jun; Lv, Guanghui; Li, Haohong; Lu, Jian; Ding, Ran; Li, Xingyi; Guang, Yu; Yang, Zhiqi; Qin, Han; Jin, Wenjun; Zhang, Kuan; He, Chao; Jia, Hongbo; Zeng, Shaoqun; Hu, Zhian; Nelken, Israel; Chen, Xiaowei

2017-06-01

The ability of the brain to predict future events based on the pattern of recent sensory experience is critical for guiding animal's behavior. Neocortical circuits for ongoing processing of sensory stimuli are extensively studied, but their contributions to the anticipation of upcoming sensory stimuli remain less understood. We, therefore, used in vivo cellular imaging and fiber photometry to record mouse primary auditory cortex to elucidate its role in processing anticipated stimulation. We found neuronal ensembles in layers 2/3, 4, and 5 which were activated in relationship to anticipated sound events following rhythmic stimulation. These neuronal activities correlated with the occurrence of anticipatory motor responses in an auditory learning task. Optogenetic manipulation experiments revealed an essential role of such neuronal activities in producing the anticipatory behavior. These results strongly suggest that the neural circuits of primary sensory cortex are critical for coding predictive information and transforming it into anticipatory motor behavior. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Transient visual responses reset the phase of low-frequency oscillations in the skeletomotor periphery.

PubMed

Wood, Daniel K; Gu, Chao; Corneil, Brian D; Gribble, Paul L; Goodale, Melvyn A

2015-08-01

We recorded muscle activity from an upper limb muscle while human subjects reached towards peripheral targets. We tested the hypothesis that the transient visual response sweeps not only through the central nervous system, but also through the peripheral nervous system. Like the transient visual response in the central nervous system, stimulus-locked muscle responses (< 100 ms) were sensitive to stimulus contrast, and were temporally and spatially dissociable from voluntary orienting activity. Also, the arrival of visual responses reduced the variability of muscle activity by resetting the phase of ongoing low-frequency oscillations. This latter finding critically extends the emerging evidence that the feedforward visual sweep reduces neural variability via phase resetting. We conclude that, when sensory information is relevant to a particular effector, detailed information about the sensorimotor transformation, even from the earliest stages, is found in the peripheral nervous system. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Single-trial dynamics of motor cortex and their applications to brain-machine interfaces

PubMed Central

Kao, Jonathan C.; Nuyujukian, Paul; Ryu, Stephen I.; Churchland, Mark M.; Cunningham, John P.; Shenoy, Krishna V.

2015-01-01

Increasing evidence suggests that neural population responses have their own internal drive, or dynamics, that describe how the neural population evolves through time. An important prediction of neural dynamical models is that previously observed neural activity is informative of noisy yet-to-be-observed activity on single-trials, and may thus have a denoising effect. To investigate this prediction, we built and characterized dynamical models of single-trial motor cortical activity. We find these models capture salient dynamical features of the neural population and are informative of future neural activity on single trials. To assess how neural dynamics may beneficially denoise single-trial neural activity, we incorporate neural dynamics into a brain–machine interface (BMI). In online experiments, we find that a neural dynamical BMI achieves substantially higher performance than its non-dynamical counterpart. These results provide evidence that neural dynamics beneficially inform the temporal evolution of neural activity on single trials and may directly impact the performance of BMIs. PMID:26220660
Cannabis Use and Memory Brain Function in Adolescent Boys: A Cross-Sectional Multicenter Functional Magnetic Resonance Imaging Study

ERIC Educational Resources Information Center

Jager, Gerry; Block, Robert I.; Luijten, Maartje; Ramsey, Nick F.

2010-01-01

Objective: Early-onset cannabis use has been associated with later use/abuse, mental health problems (psychosis, depression), and abnormal development of cognition and brain function. During adolescence, ongoing neurodevelopmental maturation and experience shape the neural circuitry underlying complex cognitive functions such as memory and…
Hierarchically Organized Behavior and Its Neural Foundations: A Reinforcement Learning Perspective

ERIC Educational Resources Information Center

Botvinick, Matthew M.; Niv, Yael; Barto, Andrew C.

2009-01-01

Research on human and animal behavior has long emphasized its hierarchical structure--the divisibility of ongoing behavior into discrete tasks, which are comprised of subtask sequences, which in turn are built of simple actions. The hierarchical structure of behavior has also been of enduring interest within neuroscience, where it has been widely…
Opaque for the Reader but Transparent for the Brain: Neural Signatures of Morphological Complexity

ERIC Educational Resources Information Center

Meinzer, Marcus; Lahiri, Aditi; Flaisch, Tobias; Hannemann, Ronny; Eulitz, Carsten

2009-01-01

Within linguistics, words with a complex internal structure are commonly assumed to be decomposed into their constituent morphemes (e.g., un-help-ful). Nevertheless, an ongoing debate concerns the brain structures that subserve this process. Using functional magnetic resonance imaging, the present study varied the internal complexity of derived…
Separable Neural Mechanisms Contribute to Feedback Processing in a Rule-Learning Task

ERIC Educational Resources Information Center

Zanolie, K.; Van Leijenhorst, L.; Rombouts, S. A. R. B.; Crone, E. A.

2008-01-01

To adjust performance appropriately to environmental demands, it is important to monitor ongoing action and process performance feedback for possible errors. In this study, we used fMRI to test whether medial prefrontal cortex (PFC)/anterior cingulate cortex (ACC) and dorsolateral (DL) PFC have different roles in feedback processing. Twenty adults…
Volitional control of attention and brain activation in dual task performance.

PubMed

Newman, Sharlene D; Keller, Timothy A; Just, Marcel Adam

2007-02-01

This study used functional MRI (fMRI) to examine the neural effects of willfully allocating one's attention to one of two ongoing tasks. In a dual task paradigm, participants were instructed to focus either on auditory sentence comprehension, mental rotation, or both. One of the major findings is that the distribution of brain activation was amenable to strategic control, such that the amount of activation per task was systematically related to the attention-dividing instructions. The activation in language processing regions was lower when attending to mental rotation than when attending to the sentences, and the activation in visuospatial processing regions was lower when attending to sentences than when attending to mental rotations. Additionally, the activation was found to be underadditive, with the dual-task condition eliciting less activation than the sum of the attend sentence and attend rotation conditions. We also observed a laterality shift across conditions within language-processing regions, with the attend sentence condition showing bilateral activation, while the dual task condition showed a left hemispheric dominance. This shift suggests multiple language-processing modes and may explain the underadditivity in activation observed in the current and previous studies.
Neural correlates of instrumental responding in the context of alcohol-related cues index disorder severity and relapse risk.

PubMed

Schad, Daniel J; Garbusow, Maria; Friedel, Eva; Sommer, Christian; Sebold, Miriam; Hägele, Claudia; Bernhardt, Nadine; Nebe, Stephan; Kuitunen-Paul, Sören; Liu, Shuyan; Eichmann, Uta; Beck, Anne; Wittchen, Hans-Ulrich; Walter, Henrik; Sterzer, Philipp; Zimmermann, Ulrich S; Smolka, Michael N; Schlagenhauf, Florian; Huys, Quentin J M; Heinz, Andreas; Rapp, Michael A

2018-01-08

The influence of Pavlovian conditioned stimuli on ongoing behavior may contribute to explaining how alcohol cues stimulate drug seeking and intake. Using a Pavlovian-instrumental transfer task, we investigated the effects of alcohol-related cues on approach behavior (i.e., instrumental response behavior) and its neural correlates, and related both to the relapse after detoxification in alcohol-dependent patients. Thirty-one recently detoxified alcohol-dependent patients and 24 healthy controls underwent instrumental training, where approach or non-approach towards initially neutral stimuli was reinforced by monetary incentives. Approach behavior was tested during extinction with either alcohol-related or neutral stimuli (as Pavlovian cues) presented in the background during functional magnetic resonance imaging (fMRI). Patients were subsequently followed up for 6 months. We observed that alcohol-related background stimuli inhibited the approach behavior in detoxified alcohol-dependent patients (t = - 3.86, p < .001), but not in healthy controls (t = - 0.92, p = .36). This behavioral inhibition was associated with neural activation in the nucleus accumbens (NAcc) (t (30) = 2.06, p < .05). Interestingly, both the effects were only present in subsequent abstainers, but not relapsers and in those with mild but not severe dependence. Our data show that alcohol-related cues can acquire inhibitory behavioral features typical of aversive stimuli despite being accompanied by a stronger NAcc activation, suggesting salience attribution. The fact that these findings are restricted to abstinence and milder illness suggests that they may be potential resilience factors. LeAD study, http://www.lead-studie.de , NCT01679145.
Architectural design for a low cost FPGA-based traffic signal detection system in vehicles

NASA Astrophysics Data System (ADS)

López, Ignacio; Salvador, Rubén; Alarcón, Jaime; Moreno, Félix

2007-05-01

In this paper we propose an architecture for an embedded traffic signal detection system. Development of Advanced Driver Assistance Systems (ADAS) is one of the major trends of research in automotion nowadays. Examples of past and ongoing projects in the field are CHAMELEON ("Pre-Crash Application all around the vehicle" IST 1999-10108), PREVENT (Preventive and Active Safety Applications, FP6-507075, http://www.prevent-ip.org/) and AVRT in the US (Advanced Vision-Radar Threat Detection (AVRT): A Pre-Crash Detection and Active Safety System). It can be observed a major interest in systems for real-time analysis of complex driving scenarios, evaluating risk and anticipating collisions. The system will use a low cost CCD camera on the dashboard facing the road. The images will be processed by an Altera Cyclone family FPGA. The board does median and Sobel filtering of the incoming frames at PAL rate, and analyzes them for several categories of signals. The result is conveyed to the driver. The scarce resources provided by the hardware require an architecture developed for optimal use. The system will use a combination of neural networks and an adapted blackboard architecture. Several neural networks will be used in sequence for image analysis, by reconfiguring a single, generic hardware neural network in the FPGA. This generic network is optimized for speed, in order to admit several executions within the frame rate. The sequence will follow the execution cycle of the blackboard architecture. The global, blackboard architecture being developed and the hardware architecture for the generic, reconfigurable FPGA perceptron will be explained in this paper. The project is still at an early stage. However, some hardware implementation results are already available and will be offered in the paper.
Working Memory in the Service of Executive Control Functions.

PubMed

Mansouri, Farshad A; Rosa, Marcello G P; Atapour, Nafiseh

2015-01-01

Working memory is a type of short-term memory which has a crucial cognitive function that supports ongoing and upcoming behaviors, allowing storage of information across delay periods. The content of this memory may typically include tangible information about features such as the shape, color or texture of an object, and its location and motion relative to the body, as well as phonological information. The neural correlate of working memory has been found in different brain areas that are involved in organizing perceptual or motor functions. In particular, neuronal activity in prefrontal areas encodes task-related information corresponding to working memory across delay periods, and lesions in the prefrontal cortex severely affect the ability to retain this type of memory. Recent studies have further expanded the scope and possible role of working memory by showing that information of a more abstract nature (including a behavior-guiding rule, or the occurrence of a conflict in information processing) can also be maintained in short-term memory, and used for adjusting the allocation of executive control in dynamic environments. It has also been shown that neuronal activity in the prefrontal cortex encodes and maintains information about such abstract entities. These findings suggest that the prefrontal cortex plays crucial roles in the organization of goal-directed behavior by supporting many different mnemonic processes, which maintain a wide range of information required for the executive control of ongoing and upcoming behaviors.
Neuronal activity during development: permissive or instructive?

PubMed

Crair, M C

1999-02-01

Experimental studies over the past year have shown that neural activity has a range of effects on the development of neural pathways. Although activity appears unimportant for establishing many aspects of the gross morphology and topology of the brain, there are many cases where the presence of neural activity is essential for the formation of a mature system of neural connections; in some instances, the pattern of neural activity actually orchestrates the final arrangement of neural connections.
Neural and behavioral correlates of selective stopping: Evidence for a different strategy adoption.

PubMed

Sánchez-Carmona, Alberto J; Albert, Jacobo; Hinojosa, José A

2016-10-01

The present study examined the neural and behavioral correlates of selective stopping, a form of inhibition that has scarcely been investigated. The selectivity of the inhibitory process is needed when individuals have to deal with an environment filled with multiple stimuli, some of which require inhibition and some of which do not. The stimulus-selective stop-signal task has been used to explore this issue assuming that all participants interrupt their ongoing responses selectively to stop but not to ignore signals. However, recent behavioral evidence suggests that some individuals do not carry out the task as experimenters expect, since they seemed to interrupt their response non-selectively to both signals. In the present study, we detected and controlled the cognitive strategy adopted by participants (n=57) when they performed a stimulus-selective stop-signal task before comparing brain activation between conditions. In order to determine both the onset and the end of the response cancellation process underlying each strategy and to fully take advantage of the precise temporal resolution of event-related potentials, we used a mass univariate approach. Source localization techniques were also employed to estimate the neural underpinnings of the effects observed at the scalp level. Our results from scalp and source level analysis support the behavioral-based strategy classification. Specific effects were observed depending on the strategy adopted by participants. Thus, when contrasting successful stop versus ignore conditions, increased activation was only evident for subjects who were classified as using a strategy whereby the response interruption process was selective to stop trials. This increased activity was observed during the P3 time window in several left-lateralized brain regions, including middle and inferior frontal gyri, as well as parietal and insular cortices. By contrast, in those participants who used a strategy characterized by stopping non-selectively, no activation differences between successful stop and ignore conditions were observed at the estimated time at which response interruption process occurs. Overall, results from the current study highlight the importance of controlling for the different strategies adopted by participants to perform selective stopping tasks before analyzing brain activation patterns. Copyright © 2016 Elsevier Inc. All rights reserved.
Neural Responses to Heartbeats in the Default Network Encode the Self in Spontaneous Thoughts.

PubMed

Babo-Rebelo, Mariana; Richter, Craig G; Tallon-Baudry, Catherine

2016-07-27

The default network (DN) has been consistently associated with self-related cognition, but also to bodily state monitoring and autonomic regulation. We hypothesized that these two seemingly disparate functional roles of the DN are functionally coupled, in line with theories proposing that selfhood is grounded in the neural monitoring of internal organs, such as the heart. We measured with magnetoencephalograhy neural responses evoked by heartbeats while human participants freely mind-wandered. When interrupted by a visual stimulus at random intervals, participants scored the self-relatedness of the interrupted thought. They evaluated their involvement as the first-person perspective subject or agent in the thought ("I"), and on another scale to what degree they were thinking about themselves ("Me"). During the interrupted thought, neural responses to heartbeats in two regions of the DN, the ventral precuneus and the ventromedial prefrontal cortex, covaried, respectively, with the "I" and the "Me" dimensions of the self, even at the single-trial level. No covariation between self-relatedness and peripheral autonomic measures (heart rate, heart rate variability, pupil diameter, electrodermal activity, respiration rate, and phase) or alpha power was observed. Our results reveal a direct link between selfhood and neural responses to heartbeats in the DN and thus directly support theories grounding selfhood in the neural monitoring of visceral inputs. More generally, the tight functional coupling between self-related processing and cardiac monitoring observed here implies that, even in the absence of measured changes in peripheral bodily measures, physiological and cognitive functions have to be considered jointly in the DN. The default network (DN) has been consistently associated with self-processing but also with autonomic regulation. We hypothesized that these two functions could be functionally coupled in the DN, inspired by theories according to which selfhood is grounded in the neural monitoring of internal organs. Using magnetoencephalography, we show that heartbeat-evoked responses (HERs) in the DN covary with the self-relatedness of ongoing spontaneous thoughts. HER amplitude in the ventral precuneus covaried with the "I" self-dimension, whereas HER amplitude in the ventromedial prefrontal cortex encoded the "Me" self-dimension. Our experimental results directly support theories rooting selfhood in the neural monitoring of internal organs. We propose a novel functional framework for the DN, where self-processing is coupled with physiological monitoring. Copyright © 2016 Babo-Rebelo et al.
Neural Responses to Heartbeats in the Default Network Encode the Self in Spontaneous Thoughts

PubMed Central

Babo-Rebelo, Mariana; Richter, Craig G.

2016-01-01

The default network (DN) has been consistently associated with self-related cognition, but also to bodily state monitoring and autonomic regulation. We hypothesized that these two seemingly disparate functional roles of the DN are functionally coupled, in line with theories proposing that selfhood is grounded in the neural monitoring of internal organs, such as the heart. We measured with magnetoencephalograhy neural responses evoked by heartbeats while human participants freely mind-wandered. When interrupted by a visual stimulus at random intervals, participants scored the self-relatedness of the interrupted thought. They evaluated their involvement as the first-person perspective subject or agent in the thought (“I”), and on another scale to what degree they were thinking about themselves (“Me”). During the interrupted thought, neural responses to heartbeats in two regions of the DN, the ventral precuneus and the ventromedial prefrontal cortex, covaried, respectively, with the “I” and the “Me” dimensions of the self, even at the single-trial level. No covariation between self-relatedness and peripheral autonomic measures (heart rate, heart rate variability, pupil diameter, electrodermal activity, respiration rate, and phase) or alpha power was observed. Our results reveal a direct link between selfhood and neural responses to heartbeats in the DN and thus directly support theories grounding selfhood in the neural monitoring of visceral inputs. More generally, the tight functional coupling between self-related processing and cardiac monitoring observed here implies that, even in the absence of measured changes in peripheral bodily measures, physiological and cognitive functions have to be considered jointly in the DN. SIGNIFICANCE STATEMENT The default network (DN) has been consistently associated with self-processing but also with autonomic regulation. We hypothesized that these two functions could be functionally coupled in the DN, inspired by theories according to which selfhood is grounded in the neural monitoring of internal organs. Using magnetoencephalography, we show that heartbeat-evoked responses (HERs) in the DN covary with the self-relatedness of ongoing spontaneous thoughts. HER amplitude in the ventral precuneus covaried with the “I” self-dimension, whereas HER amplitude in the ventromedial prefrontal cortex encoded the “Me” self-dimension. Our experimental results directly support theories rooting selfhood in the neural monitoring of internal organs. We propose a novel functional framework for the DN, where self-processing is coupled with physiological monitoring. PMID:27466329
ShapeShop: Towards Understanding Deep Learning Representations via Interactive Experimentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hohman, Frederick M.; Hodas, Nathan O.; Chau, Duen Horng

Deep learning is the driving force behind many recent technologies; however, deep neural networks are often viewed as “black-boxes” due to their internal complexity that is hard to understand. Little research focuses on helping people explore and understand the relationship between a user’s data and the learned representations in deep learning models. We present our ongoing work, ShapeShop, an interactive system for visualizing and understanding what semantics a neural network model has learned. Built using standard web technologies, ShapeShop allows users to experiment with and compare deep learning models to help explore the robustness of image classifiers.
From wheels to wings with evolutionary spiking circuits.

PubMed

Floreano, Dario; Zufferey, Jean-Christophe; Nicoud, Jean-Daniel

2005-01-01

We give an overview of the EPFL indoor flying project, whose goal is to evolve neural controllers for autonomous, adaptive, indoor micro-flyers. Indoor flight is still a challenge because it requires miniaturization, energy efficiency, and control of nonlinear flight dynamics. This ongoing project consists of developing a flying, vision-based micro-robot, a bio-inspired controller composed of adaptive spiking neurons directly mapped into digital microcontrollers, and a method to evolve such a neural controller without human intervention. This article describes the motivation and methodology used to reach our goal as well as the results of a number of preliminary experiments on vision-based wheeled and flying robots.
A preliminary study of the effects of working memory training on brain function in Attention-Deficit/Hyperactivity Disorder

PubMed Central

Stevens, Michael C.; Gaynor, Alexandra; Bessette, Katie L.; Pearlson, Godfrey D.

2015-01-01

Working memory (WM) training improves WM ability in Attention-Deficit/Hyperactivity Disorder (ADHD), but its efficacy for non-cognitive ADHD impairments ADHD has been sharply debated. The purpose of this preliminary study was to characterize WM training-related changes in ADHD brain function and see if they were linked to clinical improvement. We examined 18 adolescents diagnosed with DSM-IV Combined-subtype ADHD before and after 25 sessions of WM training using a frequently employed approach (CogmedTM) using a nonverbal Sternberg WM fMRI task, neuropsychological tests, and participant- and parent-reports of ADHD symptom severity and associated functional impairment. Whole brain SPM8 analyses identified ADHD activation deficits compared to 18 non-ADHD control participants, then tested whether impaired ADHD frontoparietal brain activation would increase following WM training. Post hoc tests examined the relationships between neural changes and neurocognitive or clinical improvements. As predicted, WM training increased WM performance, ADHD clinical functioning, and WM-related ADHD brain activity in several frontal, parietal and temporal lobe regions. Increased left inferior frontal sulcus region activity was seen in all Encoding, Maintenance, and Retrieval Sternberg task phases. ADHD symptom severity improvements were most often positively correlated with activation gains in brain regions known to be engaged for WM-related executive processing; improvement of different symptom types had different neural correlates. The responsiveness of both amodal WM frontoparietal circuits and executive process-specific WM brain regions was altered by WM training. The latter might represent a promising, relatively unexplored treatment target for researchers seeking to optimize clinical response in ongoing ADHD WM training development efforts. PMID:26138580

Influence of neural adaptation on dynamics and equilibrium state of neural activities in a ring neural network

NASA Astrophysics Data System (ADS)

Takiyama, Ken

2017-12-01

How neural adaptation affects neural information processing (i.e. the dynamics and equilibrium state of neural activities) is a central question in computational neuroscience. In my previous works, I analytically clarified the dynamics and equilibrium state of neural activities in a ring-type neural network model that is widely used to model the visual cortex, motor cortex, and several other brain regions. The neural dynamics and the equilibrium state in the neural network model corresponded to a Bayesian computation and statistically optimal multiple information integration, respectively, under a biologically inspired condition. These results were revealed in an analytically tractable manner; however, adaptation effects were not considered. Here, I analytically reveal how the dynamics and equilibrium state of neural activities in a ring neural network are influenced by spike-frequency adaptation (SFA). SFA is an adaptation that causes gradual inhibition of neural activity when a sustained stimulus is applied, and the strength of this inhibition depends on neural activities. I reveal that SFA plays three roles: (1) SFA amplifies the influence of external input in neural dynamics; (2) SFA allows the history of the external input to affect neural dynamics; and (3) the equilibrium state corresponds to the statistically optimal multiple information integration independent of the existence of SFA. In addition, the equilibrium state in a ring neural network model corresponds to the statistically optimal integration of multiple information sources under biologically inspired conditions, independent of the existence of SFA.
A chemical screen in zebrafish embryonic cells establishes that Akt activation is required for neural crest development

PubMed Central

Ciarlo, Christie; Kaufman, Charles K; Kinikoglu, Beste; Michael, Jonathan; Yang, Song; D′Amato, Christopher; Blokzijl-Franke, Sasja; den Hertog, Jeroen; Schlaeger, Thorsten M; Zhou, Yi; Liao, Eric

2017-01-01

The neural crest is a dynamic progenitor cell population that arises at the border of neural and non-neural ectoderm. The inductive roles of FGF, Wnt, and BMP at the neural plate border are well established, but the signals required for subsequent neural crest development remain poorly characterized. Here, we conducted a screen in primary zebrafish embryo cultures for chemicals that disrupt neural crest development, as read out by crestin:EGFP expression. We found that the natural product caffeic acid phenethyl ester (CAPE) disrupts neural crest gene expression, migration, and melanocytic differentiation by reducing Sox10 activity. CAPE inhibits FGF-stimulated PI3K/Akt signaling, and neural crest defects in CAPE-treated embryos are suppressed by constitutively active Akt1. Inhibition of Akt activity by constitutively active PTEN similarly decreases crestin expression and Sox10 activity. Our study has identified Akt as a novel intracellular pathway required for neural crest differentiation. PMID:28832322
Driving working memory with frequency-tuned noninvasive brain stimulation.

PubMed

Albouy, Philippe; Baillet, Sylvain; Zatorre, Robert J

2018-04-29

Frequency-tuned noninvasive brain stimulation is a recent approach in cognitive neuroscience that involves matching the frequency of transcranially applied electromagnetic fields to that of specific oscillatory components of the underlying neurophysiology. The objective of this method is to modulate ongoing/intrinsic brain oscillations, which correspond to rhythmic fluctuations of neural excitability, to causally change behavior. We review the impact of frequency-tuned noninvasive brain stimulation on the research field of human working memory. We argue that this is a powerful method to probe and understand the mechanisms of memory functions, targeting specifically task-related oscillatory dynamics, neuronal representations, and brain networks. We report the main behavioral and neurophysiological outcomes published to date, in particular, how functionally relevant oscillatory signatures in signal power and interregional connectivity yield causal changes of working memory abilities. We also present recent developments of the technique that aim to modulate cross-frequency coupling in polyrhythmic neural activity. Overall, the method has led to significant advances in our understanding of the mechanisms of systems neuroscience, and the role of brain oscillations in cognition and behavior. We also emphasize the translational impact of noninvasive brain stimulation techniques in the development of therapeutic approaches. © 2018 New York Academy of Sciences.
Quantitative theory of driven nonlinear brain dynamics.

PubMed

Roberts, J A; Robinson, P A

2012-09-01

Strong periodic stimuli such as bright flashing lights evoke nonlinear responses in the brain and interact nonlinearly with ongoing cortical activity, but the underlying mechanisms for these phenomena are poorly understood at present. The dominant features of these experimentally observed dynamics are reproduced by the dynamics of a quantitative neural field model subject to periodic drive. Model power spectra over a range of drive frequencies show agreement with multiple features of experimental measurements, exhibiting nonlinear effects including entrainment over a range of frequencies around the natural alpha frequency f(α), subharmonic entrainment near 2f(α), and harmonic generation. Further analysis of the driven dynamics as a function of the drive parameters reveals rich nonlinear dynamics that is predicted to be observable in future experiments at high drive amplitude, including period doubling, bistable phase-locking, hysteresis, wave mixing, and chaos indicated by positive Lyapunov exponents. Moreover, photosensitive seizures are predicted for physiologically realistic model parameters yielding bistability between healthy and seizure dynamics. These results demonstrate the applicability of neural field models to the new regime of periodically driven nonlinear dynamics, enabling interpretation of experimental data in terms of specific generating mechanisms and providing new tests of the theory. Copyright © 2012 Elsevier Inc. All rights reserved.
Variability of perceptual multistability: from brain state to individual trait

PubMed Central

Kleinschmidt, Andreas; Sterzer, Philipp; Rees, Geraint

2012-01-01

Few phenomena are as suitable as perceptual multistability to demonstrate that the brain constructively interprets sensory input. Several studies have outlined the neural circuitry involved in generating perceptual inference but only more recently has the individual variability of this inferential process been appreciated. Studies of the interaction of evoked and ongoing neural activity show that inference itself is not merely a stimulus-triggered process but is related to the context of the current brain state into which the processing of external stimulation is embedded. As brain states fluctuate, so does perception of a given sensory input. In multistability, perceptual fluctuation rates are consistent for a given individual but vary considerably between individuals. There has been some evidence for a genetic basis for these individual differences and recent morphometric studies of parietal lobe regions have identified neuroanatomical substrates for individual variability in spontaneous switching behaviour. Moreover, disrupting the function of these latter regions by transcranial magnetic stimulation yields systematic interference effects on switching behaviour, further arguing for a causal role of these regions in perceptual inference. Together, these studies have advanced our understanding of the biological mechanisms by which the brain constructs the contents of consciousness from sensory input. PMID:22371620
Progesterone from maternal circulation binds to progestin receptors in fetal brain.

PubMed

Wagner, Christine K; Quadros-Mennella, Princy

2017-06-01

Steroid hormones activate nuclear receptors which, as transcription factors, can regulate critical aspects of neural development. Many regions of the rat forebrain, midbrain and hindbrain express progestin receptors (PR) during perinatal life, suggesting that progesterone may play an important role in the development of the brain. An immunohistochemical approach using two antibodies with differential recognition of ligand-bound PR was used to examine whether fetuses are exposed to maternal progesterone during pregnancy and whether progesterone from maternal circulation can bind to PR within the fetal brain. Findings demonstrate that maternal and fetal serum progesterone levels are positively correlated at the end of gestation, suggesting a common source of progesterone in mothers and fetuses (e.g., the maternal ovary). Additional findings suggest that administration of exogenous progesterone to mothers not only increases fetal serum progesterone levels within 2 h, but appears to increase ligand-bound PR in fetal brain. These findings suggest that progesterone of maternal origin may play a previously overlooked role in neural development. In addition, there are implications for the ongoing prophylactic use of synthetic progestins in pregnant women for the prevention of premature birth. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 767-774, 2017. © 2016 Wiley Periodicals, Inc.
Effects of therapeutic interventions for foster children on behavioral problems, caregiver attachment, and stress regulatory neural systems.

PubMed

Fisher, Philip A; Gunnar, Megan R; Dozier, Mary; Bruce, Jacqueline; Pears, Katherine C

2006-12-01

Young children in foster care are exposed to high levels of stress. These experiences place foster children at risk for poor social, academic, and mental heath outcomes. The role of adverse events in stimulating neurobiological stress responses presumably plays a role in shaping neural systems that contribute to these problems. Systematic and developmentally well-timed interventions might have the potential to change developmental trajectories and promote resilience. Moreover, understanding how specific dimensions of early adversity affect underlying stress response systems and how alterations in these systems are related to later psychosocial outcomes might facilitate more precise and targeted interventions. Data are drawn from two ongoing randomized trials involving foster infants/toddlers and preschoolers. Consistent with prior animal models of early adversity, these studies have shown that early adversity-particularly neglect, younger age at first foster placement, and higher number of placements-is associated with altered hypothalamic-pituitary-adrenal (HPA) axis function. The interventions under investigation have produced evidence that it is possible to impact many areas that have been negatively affected by early stress, including HPA axis activity, behavior, and attachment to caregivers.
The Role of Oscillatory Phase in Determining the Temporal Organization of Perception: Evidence from Sensory Entrainment.

PubMed

Ronconi, Luca; Melcher, David

2017-11-01

Recent behavioral, neuroimaging, and neurophysiological studies have renewed the idea that the information processing within different temporal windows is linked to the phase and/or frequency of the ongoing oscillations, predominantly in the theta/alpha band (∼4-7 and 8-12 Hz, respectively). However, being correlational in nature, this evidence might reflect a nonfunctional byproduct rather than having a causal role. A more direct link can be shown with methods that manipulate oscillatory activity. Here, we used audiovisual entrainment at different frequencies in the prestimulus period of a temporal integration/segregation task. We hypothesized that entrainment would align ongoing oscillations and drive them toward the stimulation frequency. To reveal behavioral oscillations in temporal perception after the entrainment, we sampled the segregation/integration performance densely in time. In Experiment 1, two groups of human participants (both males and females) received stimulation either at the lower or the upper boundary of the alpha band (∼8.5 vs 11.5 Hz). For both entrainment frequencies, we found a phase alignment of the perceptual oscillation across subjects, but with two different power spectra that peaked near the entrainment frequency. These results were confirmed when perceptual oscillations were characterized in the time domain with sinusoidal fittings. In Experiment 2, we replicated the findings in a within-subject design, extending the results for frequencies in the theta (∼6.5 Hz), but not in the beta (∼15 Hz), range. Overall, these findings show that temporal segregation can be modified by sensory entrainment, providing evidence for a critical role of ongoing oscillations in the temporal organization of perception. SIGNIFICANCE STATEMENT The continuous flow of sensory input is not processed in an analog fashion, but rather is grouped by the perceptual system over time. Recent studies pinpointed the phase and/or frequency of the neural oscillations in the theta/alpha band (∼4-12 Hz) as possible mechanisms underlying temporal windows in perception. Here, we combined two innovative methodologies to provide more direct support for this evidence. We used sensory entrainment to align neural oscillations to different frequencies and then characterized the resultant perceptual oscillation with a temporal dense sampling of the integration/segregation performance. Our results provide the first evidence that the frequency of temporal segregation can be modified by sensory entrainment, supporting a critical role of ongoing oscillations in the integration/segregation of information over time. Copyright © 2017 Ronconi and Melcher.
Brain games: toward a neuroecology of social behavior.

PubMed

Gariépy, Jean-François; Chang, Steve W C; Platt, Michael L

2013-08-01

In the target article, Schilbach et al. defend a "second-person neuroscience" perspective that focuses on the neural basis of social cognition during live, ongoing interactions between individuals. We argue that a second-person neuroscience would benefit from formal approaches borrowed from economics and behavioral ecology and that it should be extended to social interactions in nonhuman animals.
Observational Learning in Mice Can Be Prevented by Medial Prefrontal Cortex Stimulation and Enhanced by Nucleus Accumbens Stimulation

ERIC Educational Resources Information Center

Jurado-Parras, M. Teresa; Gruart, Agnes; Delgado-Garcia, Jose M.

2012-01-01

The neural structures involved in ongoing appetitive and/or observational learning behaviors remain largely unknown. Operant conditioning and observational learning were evoked and recorded in a modified Skinner box provided with an on-line video recording system. Mice improved their acquisition of a simple operant conditioning task by…
Developmental effects of aggressive behavior in male adolescents assessed with structural and functional brain imaging

PubMed Central

Strenziok, Maren; Krueger, Frank; Heinecke, Armin; Lenroot, Rhoshel K.; Knutson, Kristine M.; van der Meer, Elke

2011-01-01

Aggressive behavior is common during adolescence. Although aggression-related functional changes in the ventromedial prefrontal cortex (vmPFC) and frontopolar cortex (FPC) have been reported in adults, the neural correlates of aggressive behavior in adolescents, particularly in the context of structural neurodevelopment, are obscure. We used functional and structural magnetic resonance imaging (MRI) to measure the blood oxygenation level-depended signal and cortical thickness. In a block-designed experiment, 14–17-year old adolescents imagined aggressive and non-aggressive interactions with a peer. We show reduced vmPFC activation associated with imagined aggressive behavior as well as enhanced aggression-related activation and cortical thinning in the FPC with increasing age. Changes in FPC activation were also associated with judgments of the severity of aggressive acts. Reduced vmPFC activation was associated with greater aggression indicating its normal function is to exert inhibitory control over aggressive impulses. Concurrent FPC activation likely reflects foresight of harmful consequences that result from aggressive acts. The correlation of age-dependent activation changes and cortical thinning demonstrates ongoing maturation of the FPC during adolescence towards a refinement of social and cognitive information processing that can potentially facilitate mature social behavior in aggressive contexts. PMID:19770220
Psychological Processing in Chronic Pain: A Neural Systems Approach

PubMed Central

Simons, Laura; Elman, Igor; Borsook, David

2014-01-01

Our understanding of chronic pain involves complex brain circuits that include sensory, emotional, cognitive and interoceptive processing. The feed-forward interactions between physical (e.g., trauma) and emotional pain and the consequences of altered psychological status on the expression of pain have made the evaluation and treatment of chronic pain a challenge in the clinic. By understanding the neural circuits involved in psychological processes, a mechanistic approach to the implementation of psychology-based treatments may be better understood. In this review we evaluate some of the principle processes that may be altered as a consequence of chronic pain in the context of localized and integrated neural networks. These changes are ongoing, vary in their magnitude, and their hierarchical manifestations, and may be temporally and sequentially altered by treatments, and all contribute to an overall pain phenotype. Furthermore, we link altered psychological processes to specific evidence-based treatments to put forth a model of pain neuroscience psychology. PMID:24374383
Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons.

PubMed

Ma, Ying; Shaik, Mohammed A; Kozberg, Mariel G; Kim, Sharon H; Portes, Jacob P; Timerman, Dmitriy; Hillman, Elizabeth M C

2016-12-27

Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI.
Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons

PubMed Central

Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Portes, Jacob P.; Timerman, Dmitriy

2016-01-01

Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI. PMID:27974609
Neural and Behavioral Evidence for an Online Resetting Process in Visual Working Memory.

PubMed

Balaban, Halely; Luria, Roy

2017-02-01

Visual working memory (VWM) guides behavior by holding a set of active representations and modifying them according to changes in the environment. This updating process relies on a unique mapping between each VWM representation and an actual object in the environment. Here, we destroyed this mapping by either presenting a coherent object but then breaking it into independent parts or presenting an object but then abruptly replacing it with a different object. This allowed us to introduce the neural marker and behavioral consequence of an online resetting process in humans' VWM. Across seven experiments, we demonstrate that this resetting process involves abandoning the old VWM contents because they no longer correspond to the objects in the environment. Then, VWM encodes the novel information and reestablishes the correspondence between the new representations and the objects. The resetting process was marked by a unique neural signature: a sharp drop in the amplitude of the electrophysiological index of VWM contents (the contralateral delay activity), presumably indicating the loss of the existent object-to-representation mappings. This marker was missing when an updating process occurred. Moreover, when tracking moving items, VWM failed to detect salient changes in the object's shape when these changes occurred during the resetting process. This happened despite the object being fully visible, presumably because the mapping between the object and a VWM representation was lost. Importantly, we show that resetting, its neural marker, and the behavioral cost it entails, are specific to situations that involve a destruction of the objects-to-representations correspondence. Visual working memory (VWM) maintains task-relevant information in an online state. Previous studies showed that VWM representations are accessed and modified after changes in the environment. Here, we show that this updating process critically depends on an ongoing mapping between the representations and the objects in the environment. When this mapping breaks, VWM cannot access the old representations and instead resets. The novel resetting process that we introduce removes the existing representations instead of modifying them and this process is accompanied by a unique neural marker. During the resetting process, VWM was blind to salient changes in the object's shape. The resetting process highlights the flexibility of our cognitive system in handling the dynamic environment by abruptly abandoning irrelevant schemas. Copyright © 2017 the authors 0270-6474/17/371225-15$15.00/0.
Studies of stimulus parameters for seizure disruption using neural network simulations.

PubMed

Anderson, William S; Kudela, Pawel; Cho, Jounhong; Bergey, Gregory K; Franaszczuk, Piotr J

2007-08-01

A large scale neural network simulation with realistic cortical architecture has been undertaken to investigate the effects of external electrical stimulation on the propagation and evolution of ongoing seizure activity. This is an effort to explore the parameter space of stimulation variables to uncover promising avenues of research for this therapeutic modality. The model consists of an approximately 800 mum x 800 mum region of simulated cortex, and includes seven neuron classes organized by cortical layer, inhibitory or excitatory properties, and electrophysiological characteristics. The cell dynamics are governed by a modified version of the Hodgkin-Huxley equations in single compartment format. Axonal connections are patterned after histological data and published models of local cortical wiring. Stimulation induced action potentials take place at the axon initial segments, according to threshold requirements on the applied electric field distribution. Stimulation induced action potentials in horizontal axonal branches are also separately simulated. The calculations are performed on a 16 node distributed 32-bit processor system. Clear differences in seizure evolution are presented for stimulated versus the undisturbed rhythmic activity. Data is provided for frequency dependent stimulation effects demonstrating a plateau effect of stimulation efficacy as the applied frequency is increased from 60 to 200 Hz. Timing of the stimulation with respect to the underlying rhythmic activity demonstrates a phase dependent sensitivity. Electrode height and position effects are also presented. Using a dipole stimulation electrode arrangement, clear orientation effects of the dipole with respect to the model connectivity is also demonstrated. A sensitivity analysis of these results as a function of the stimulation threshold is also provided.
Estimating endogenous changes in task performance from EEG

PubMed Central

Touryan, Jon; Apker, Gregory; Lance, Brent J.; Kerick, Scott E.; Ries, Anthony J.; McDowell, Kaleb

2014-01-01

Brain wave activity is known to correlate with decrements in behavioral performance as individuals enter states of fatigue, boredom, or low alertness.Many BCI technologies are adversely affected by these changes in user state, limiting their application and constraining their use to relatively short temporal epochs where behavioral performance is likely to be stable. Incorporating a passive BCI that detects when the user is performing poorly at a primary task, and adapts accordingly may prove to increase overall user performance. Here, we explore the potential for extending an established method to generate continuous estimates of behavioral performance from ongoing neural activity; evaluating the extended method by applying it to the original task domain, simulated driving; and generalizing the method by applying it to a BCI-relevant perceptual discrimination task. Specifically, we used EEG log power spectra and sequential forward floating selection (SFFS) to estimate endogenous changes in behavior in both a simulated driving task and a perceptual discrimination task. For the driving task the average correlation coefficient between the actual and estimated lane deviation was 0.37 ± 0.22 (μ ± σ). For the perceptual discrimination task we generated estimates of accuracy, reaction time, and button press duration for each participant. The correlation coefficients between the actual and estimated behavior were similar for these three metrics (accuracy = 0.25 ± 0.37, reaction time = 0.33 ± 0.23, button press duration = 0.36 ± 0.30). These findings illustrate the potential for modeling time-on-task decrements in performance from concurrent measures of neural activity. PMID:24994968
Hippocampal Sharp-Wave Ripples Influence Selective Activation of the Default Mode Network

PubMed Central

Kaplan, Raphael; Adhikari, Mohit H.; Hindriks, Rikkert; Mantini, Dante; Murayama, Yusuke; Logothetis, Nikos K.; Deco, Gustavo

2016-01-01

Summary The default mode network (DMN) is a commonly observed resting-state network (RSN) that includes medial temporal, parietal, and prefrontal regions involved in episodic memory [1, 2, 3]. The behavioral relevance of endogenous DMN activity remains elusive, despite an emerging literature correlating resting fMRI fluctuations with memory performance [4, 5]—particularly in DMN regions [6, 7, 8]. Mechanistic support for the DMN’s role in memory consolidation might come from investigation of large deflections (sharp-waves) in the hippocampal local field potential that co-occur with high-frequency (>80 Hz) oscillations called ripples—both during sleep [9, 10] and awake deliberative periods [11, 12, 13]. Ripples are ideally suited for memory consolidation [14, 15], since the reactivation of hippocampal place cell ensembles occurs during ripples [16, 17, 18, 19]. Moreover, the number of ripples after learning predicts subsequent memory performance in rodents [20, 21, 22] and humans [23], whereas electrical stimulation of the hippocampus after learning interferes with memory consolidation [24, 25, 26]. A recent study in macaques showed diffuse fMRI neocortical activation and subcortical deactivation specifically after ripples [27]. Yet it is unclear whether ripples and other hippocampal neural events influence endogenous fluctuations in specific RSNs—like the DMN—unitarily. Here, we examine fMRI datasets from anesthetized monkeys with simultaneous hippocampal electrophysiology recordings, where we observe a dramatic increase in the DMN fMRI signal following ripples, but not following other hippocampal electrophysiological events. Crucially, we find increases in ongoing DMN activity after ripples, but not in other RSNs. Our results relate endogenous DMN fluctuations to hippocampal ripples, thereby linking network-level resting fMRI fluctuations with behaviorally relevant circuit-level neural dynamics. PMID:26898464
Cracking the Neural Code for Sensory Perception by Combining Statistics, Intervention, and Behavior.

PubMed

Panzeri, Stefano; Harvey, Christopher D; Piasini, Eugenio; Latham, Peter E; Fellin, Tommaso

2017-02-08

The two basic processes underlying perceptual decisions-how neural responses encode stimuli, and how they inform behavioral choices-have mainly been studied separately. Thus, although many spatiotemporal features of neural population activity, or "neural codes," have been shown to carry sensory information, it is often unknown whether the brain uses these features for perception. To address this issue, we propose a new framework centered on redefining the neural code as the neural features that carry sensory information used by the animal to drive appropriate behavior; that is, the features that have an intersection between sensory and choice information. We show how this framework leads to a new statistical analysis of neural activity recorded during behavior that can identify such neural codes, and we discuss how to combine intersection-based analysis of neural recordings with intervention on neural activity to determine definitively whether specific neural activity features are involved in a task. Copyright © 2017 Elsevier Inc. All rights reserved.
Neural constraints on learning.

PubMed

Sadtler, Patrick T; Quick, Kristin M; Golub, Matthew D; Chase, Steven M; Ryu, Stephen I; Tyler-Kabara, Elizabeth C; Yu, Byron M; Batista, Aaron P

2014-08-28

Learning, whether motor, sensory or cognitive, requires networks of neurons to generate new activity patterns. As some behaviours are easier to learn than others, we asked if some neural activity patterns are easier to generate than others. Here we investigate whether an existing network constrains the patterns that a subset of its neurons is capable of exhibiting, and if so, what principles define this constraint. We employed a closed-loop intracortical brain-computer interface learning paradigm in which Rhesus macaques (Macaca mulatta) controlled a computer cursor by modulating neural activity patterns in the primary motor cortex. Using the brain-computer interface paradigm, we could specify and alter how neural activity mapped to cursor velocity. At the start of each session, we observed the characteristic activity patterns of the recorded neural population. The activity of a neural population can be represented in a high-dimensional space (termed the neural space), wherein each dimension corresponds to the activity of one neuron. These characteristic activity patterns comprise a low-dimensional subspace (termed the intrinsic manifold) within the neural space. The intrinsic manifold presumably reflects constraints imposed by the underlying neural circuitry. Here we show that the animals could readily learn to proficiently control the cursor using neural activity patterns that were within the intrinsic manifold. However, animals were less able to learn to proficiently control the cursor using activity patterns that were outside of the intrinsic manifold. These results suggest that the existing structure of a network can shape learning. On a timescale of hours, it seems to be difficult to learn to generate neural activity patterns that are not consistent with the existing network structure. These findings offer a network-level explanation for the observation that we are more readily able to learn new skills when they are related to the skills that we already possess.

Dissipative rendering and neural network control system design

NASA Technical Reports Server (NTRS)

Gonzalez, Oscar R.

1995-01-01

Model-based control system designs are limited by the accuracy of the models of the plant, plant uncertainty, and exogenous signals. Although better models can be obtained with system identification, the models and control designs still have limitations. One approach to reduce the dependency on particular models is to design a set of compensators that will guarantee robust stability to a set of plants. Optimization over the compensator parameters can then be used to get the desired performance. Conservativeness of this approach can be reduced by integrating fundamental properties of the plant models. This is the approach of dissipative control design. Dissipative control designs are based on several variations of the Passivity Theorem, which have been proven for nonlinear/linear and continuous-time/discrete-time systems. These theorems depend not on a specific model of a plant, but on its general dissipative properties. Dissipative control design has found wide applicability in flexible space structures and robotic systems that can be configured to be dissipative. Currently, there is ongoing research to improve the performance of dissipative control designs. For aircraft systems that are not dissipative active control may be used to make them dissipative and then a dissipative control design technique can be used. It is also possible that rendering a system dissipative and dissipative control design may be combined into one step. Furthermore, the transformation of a non-dissipative system to dissipative can be done robustly. One sequential design procedure for finite dimensional linear time-invariant systems has been developed. For nonlinear plants that cannot be controlled adequately with a single linear controller, model-based techniques have additional problems. Nonlinear system identification is still a research topic. Lacking analytical models for model-based design, artificial neural network algorithms have recently received considerable attention. Using their universal approximation property, neural networks have been introduced into nonlinear control designs in several ways. Unfortunately, little work has appeared that analyzes neural network control systems and establishes margins for stability and performance. One approach for this analysis is to set up neural network control systems in the framework presented above. For example, one neural network could be used to render a system to be dissipative, a second strictly dissipative neural network controller could be used to guarantee robust stability.
Dissociable effects of local inhibitory and excitatory theta-burst stimulation on large-scale brain dynamics

PubMed Central

Sale, Martin V.; Lord, Anton; Zalesky, Andrew; Breakspear, Michael; Mattingley, Jason B.

2015-01-01

Normal brain function depends on a dynamic balance between local specialization and large-scale integration. It remains unclear, however, how local changes in functionally specialized areas can influence integrated activity across larger brain networks. By combining transcranial magnetic stimulation with resting-state functional magnetic resonance imaging, we tested for changes in large-scale integration following the application of excitatory or inhibitory stimulation on the human motor cortex. After local inhibitory stimulation, regions encompassing the sensorimotor module concurrently increased their internal integration and decreased their communication with other modules of the brain. There were no such changes in modular dynamics following excitatory stimulation of the same area of motor cortex nor were there changes in the configuration and interactions between core brain hubs after excitatory or inhibitory stimulation of the same area. These results suggest the existence of selective mechanisms that integrate local changes in neural activity, while preserving ongoing communication between brain hubs. PMID:25717162
Stuttering, Induced Fluency, and Natural Fluency: A Hierarchical Series of Activation Likelihood Estimation Meta-Analyses

PubMed Central

Budde, Kristin S.; Barron, Daniel S.; Fox, Peter T.

2015-01-01

Developmental stuttering is a speech disorder most likely due to a heritable form of developmental dysmyelination impairing the function of the speech-motor system. Speech-induced brain-activation patterns in persons who stutter (PWS) are anomalous in various ways; the consistency of these aberrant patterns is a matter of ongoing debate. Here, we present a hierarchical series of coordinate-based meta-analyses addressing this issue. Two tiers of meta-analyses were performed on a 17-paper dataset (202 PWS; 167 fluent controls). Four large-scale (top-tier) meta-analyses were performed, two for each subject group (PWS and controls). These analyses robustly confirmed the regional effects previously postulated as “neural signatures of stuttering” (Brown 2005) and extended this designation to additional regions. Two smaller-scale (lower-tier) meta-analyses refined the interpretation of the large-scale analyses: 1) a between-group contrast targeting differences between PWS and controls (stuttering trait); and 2) a within-group contrast (PWS only) of stuttering with induced fluency (stuttering state). PMID:25463820
Distorted Character Recognition Via An Associative Neural Network

NASA Astrophysics Data System (ADS)

Messner, Richard A.; Szu, Harold H.

1987-03-01

The purpose of this paper is two-fold. First, it is intended to provide some preliminary results of a character recognition scheme which has foundations in on-going neural network architecture modeling, and secondly, to apply some of the neural network results in a real application area where thirty years of effort has had little effect on providing the machine an ability to recognize distorted objects within the same object class. It is the author's belief that the time is ripe to start applying in ernest the results of over twenty years of effort in neural modeling to some of the more difficult problems which seem so hard to solve by conventional means. The character recognition scheme proposed utilizes a preprocessing stage which performs a 2-dimensional Walsh transform of an input cartesian image field, then sequency filters this spectrum into three feature bands. Various features are then extracted and organized into three sets of feature vectors. These vector patterns that are stored and recalled associatively. Two possible associative neural memory models are proposed for further investigation. The first being an outer-product linear matrix associative memory with a threshold function controlling the strength of the output pattern (similar to Kohonen's crosscorrelation approach [1]). The second approach is based upon a modified version of Grossberg's neural architecture [2] which provides better self-organizing properties due to its adaptive nature. Preliminary results of the sequency filtering and feature extraction preprocessing stage and discussion about the use of the proposed neural architectures is included.
Neural electrical activity and neural network growth.

PubMed

Gafarov, F M

2018-05-01

The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.
EEG-fMRI Bayesian framework for neural activity estimation: a simulation study

NASA Astrophysics Data System (ADS)

Croce, Pierpaolo; Basti, Alessio; Marzetti, Laura; Zappasodi, Filippo; Del Gratta, Cosimo

2016-12-01

Objective. Due to the complementary nature of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), and given the possibility of simultaneous acquisition, the joint data analysis can afford a better understanding of the underlying neural activity estimation. In this simulation study we want to show the benefit of the joint EEG-fMRI neural activity estimation in a Bayesian framework. Approach. We built a dynamic Bayesian framework in order to perform joint EEG-fMRI neural activity time course estimation. The neural activity is originated by a given brain area and detected by means of both measurement techniques. We have chosen a resting state neural activity situation to address the worst case in terms of the signal-to-noise ratio. To infer information by EEG and fMRI concurrently we used a tool belonging to the sequential Monte Carlo (SMC) methods: the particle filter (PF). Main results. First, despite a high computational cost, we showed the feasibility of such an approach. Second, we obtained an improvement in neural activity reconstruction when using both EEG and fMRI measurements. Significance. The proposed simulation shows the improvements in neural activity reconstruction with EEG-fMRI simultaneous data. The application of such an approach to real data allows a better comprehension of the neural dynamics.
EEG-fMRI Bayesian framework for neural activity estimation: a simulation study.

PubMed

Croce, Pierpaolo; Basti, Alessio; Marzetti, Laura; Zappasodi, Filippo; Gratta, Cosimo Del

2016-12-01

Due to the complementary nature of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), and given the possibility of simultaneous acquisition, the joint data analysis can afford a better understanding of the underlying neural activity estimation. In this simulation study we want to show the benefit of the joint EEG-fMRI neural activity estimation in a Bayesian framework. We built a dynamic Bayesian framework in order to perform joint EEG-fMRI neural activity time course estimation. The neural activity is originated by a given brain area and detected by means of both measurement techniques. We have chosen a resting state neural activity situation to address the worst case in terms of the signal-to-noise ratio. To infer information by EEG and fMRI concurrently we used a tool belonging to the sequential Monte Carlo (SMC) methods: the particle filter (PF). First, despite a high computational cost, we showed the feasibility of such an approach. Second, we obtained an improvement in neural activity reconstruction when using both EEG and fMRI measurements. The proposed simulation shows the improvements in neural activity reconstruction with EEG-fMRI simultaneous data. The application of such an approach to real data allows a better comprehension of the neural dynamics.
Launching AI in NASA ground systems

NASA Technical Reports Server (NTRS)

Perkins, Dorothy C.; Truszkowski, Walter F.

1990-01-01

This paper will discuss recent operational successes in implementing expert systems to support the complex functions of NASA mission control systems at the Goddard Space Flight Center, including fault detection and diagnosis for real time and engineering analysis functions in the Cosmic Background Explorer and Gamma Ray Observatory missions and automation of resource planning and scheduling functions for various missions. It will also discuss ongoing developments and prototypes that will lead to increasingly sophisticated applications of artificial intelligence. These include the use of neural networks to perform telemetry monitoring functions, the implementation of generic expert system shells that can be customized to telemetry handling functions specific to NASA control centers, the applications of AI in training and user support, the long-term potential of implementing systems based around distributed, cooperative problem solving, and the use of AI to control and assist system development activities.
Adolescent neural response to reward is related to participant sex and task motivation

PubMed Central

Alarcón, Gabriela; Cservenka, Anita; Nagel, Bonnie J.

2017-01-01

Risky decision making is prominent during adolescence, perhaps contributed to by heightened sensation seeking and ongoing maturation of reward and dopamine systems in the brain, which are, in part, modulated by sex hormones. In this study, we examined sex differences in the neural substrates of reward sensitivity during a risky decision-making task and hypothesized that compared with girls, boys would show heightened brain activation in reward-relevant regions, particularly the nucleus accumbens, during reward receipt. Further, we hypothesized that testosterone and estradiol levels would mediate this sex difference. Moreover, we predicted boys would make more risky choices on the task. While boys showed increased nucleus accumbens blood oxygen level-dependent (BOLD) response relative to girls, sex hormones did not mediate this effect. As predicted, boys made a higher percentage of risky decisions during the task. Interestingly, boys also self-reported more motivation to perform well and earn money on the task, while girls self-reported higher state anxiety prior to the scan session. Motivation to earn money partially mediated the effect of sex on nucleus accumbens activity during reward. Previous research shows that increased motivation and salience of reinforcers is linked with more robust striatal BOLD response, therefore psychosocial factors, in addition to sex, may play an important role in reward sensitivity. Elucidating neurobiological mechanisms that support adolescent sex differences in risky decision making has important implications for understanding individual differences that lead to advantageous and adverse behaviors that affect health outcomes. PMID:27816780
Acute stress evokes sexually dimorphic, stressor-specific patterns of neural activation across multiple limbic brain regions in adult rats.

PubMed

Sood, Ankit; Chaudhari, Karina; Vaidya, Vidita A

2018-03-01

Stress enhances the risk for psychiatric disorders such as anxiety and depression. Stress responses vary across sex and may underlie the heightened vulnerability to psychopathology in females. Here, we examined the influence of acute immobilization stress (AIS) and a two-day short-term forced swim stress (FS) on neural activation in multiple cortical and subcortical brain regions, implicated as targets of stress and in the regulation of neuroendocrine stress responses, in male and female rats using Fos as a neural activity marker. AIS evoked a sex-dependent pattern of neural activation within the cingulate and infralimbic subdivisions of the medial prefrontal cortex (mPFC), lateral septum (LS), habenula, and hippocampal subfields. The degree of neural activation in the mPFC, LS, and habenula was higher in males. Female rats exhibited reduced Fos positive cell numbers in the dentate gyrus hippocampal subfield, an effect not observed in males. We addressed whether the sexually dimorphic neural activation pattern noted following AIS was also observed with the short-term stress of FS. In the paraventricular nucleus of the hypothalamus and the amygdala, FS similar to AIS resulted in robust increases in neural activation in both sexes. The pattern of neural activation evoked by FS was distinct across sexes, with a heightened neural activation noted in the prelimbic mPFC subdivision and hippocampal subfields in females and differed from the pattern noted with AIS. This indicates that the sex differences in neural activation patterns observed within stress-responsive brain regions are dependent on the nature of stressor experience.
Simulation Platform: a cloud-based online simulation environment.

PubMed

Yamazaki, Tadashi; Ikeno, Hidetoshi; Okumura, Yoshihiro; Satoh, Shunji; Kamiyama, Yoshimi; Hirata, Yutaka; Inagaki, Keiichiro; Ishihara, Akito; Kannon, Takayuki; Usui, Shiro

2011-09-01

For multi-scale and multi-modal neural modeling, it is needed to handle multiple neural models described at different levels seamlessly. Database technology will become more important for these studies, specifically for downloading and handling the neural models seamlessly and effortlessly. To date, conventional neuroinformatics databases have solely been designed to archive model files, but the databases should provide a chance for users to validate the models before downloading them. In this paper, we report our on-going project to develop a cloud-based web service for online simulation called "Simulation Platform". Simulation Platform is a cloud of virtual machines running GNU/Linux. On a virtual machine, various software including developer tools such as compilers and libraries, popular neural simulators such as GENESIS, NEURON and NEST, and scientific software such as Gnuplot, R and Octave, are pre-installed. When a user posts a request, a virtual machine is assigned to the user, and the simulation starts on that machine. The user remotely accesses to the machine through a web browser and carries out the simulation, without the need to install any software but a web browser on the user's own computer. Therefore, Simulation Platform is expected to eliminate impediments to handle multiple neural models that require multiple software. Copyright © 2011 Elsevier Ltd. All rights reserved.
Reprint of: Simulation Platform: a cloud-based online simulation environment.

PubMed

Yamazaki, Tadashi; Ikeno, Hidetoshi; Okumura, Yoshihiro; Satoh, Shunji; Kamiyama, Yoshimi; Hirata, Yutaka; Inagaki, Keiichiro; Ishihara, Akito; Kannon, Takayuki; Usui, Shiro

2011-11-01

For multi-scale and multi-modal neural modeling, it is needed to handle multiple neural models described at different levels seamlessly. Database technology will become more important for these studies, specifically for downloading and handling the neural models seamlessly and effortlessly. To date, conventional neuroinformatics databases have solely been designed to archive model files, but the databases should provide a chance for users to validate the models before downloading them. In this paper, we report our on-going project to develop a cloud-based web service for online simulation called "Simulation Platform". Simulation Platform is a cloud of virtual machines running GNU/Linux. On a virtual machine, various software including developer tools such as compilers and libraries, popular neural simulators such as GENESIS, NEURON and NEST, and scientific software such as Gnuplot, R and Octave, are pre-installed. When a user posts a request, a virtual machine is assigned to the user, and the simulation starts on that machine. The user remotely accesses to the machine through a web browser and carries out the simulation, without the need to install any software but a web browser on the user's own computer. Therefore, Simulation Platform is expected to eliminate impediments to handle multiple neural models that require multiple software. Copyright © 2011 Elsevier Ltd. All rights reserved.
Regulation of Local Ambient GABA Levels via Transporter-Mediated GABA Import and Export for Subliminal Learning.

PubMed

Hoshino, Osamu

2015-06-01

Perception of supraliminal stimuli might in general be reflected in bursts of action potentials (spikes), and their memory traces could be formed through spike-timing-dependent plasticity (STDP). Memory traces for subliminal stimuli might be formed in a different manner, because subliminal stimulation evokes a fraction (but not a burst) of spikes. Simulations of a cortical neural network model showed that a subliminal stimulus that was too brief (10 msec) to perceive transiently (more than about 500 msec) depolarized stimulus-relevant principal cells and hyperpolarized stimulus-irrelevant principal cells in a subthreshold manner. This led to a small increase or decrease in ongoing-spontaneous spiking activity frequency (less than 1 Hz). Synaptic modification based on STDP during this period effectively enhanced relevant synaptic weights, by which subliminal learning was improved. GABA transporters on GABAergic interneurons modulated local levels of ambient GABA. Ambient GABA molecules acted on extrasynaptic receptors, provided principal cells with tonic inhibitory currents, and contributed to achieving the subthreshold neuronal state. We suggest that ongoing-spontaneous synaptic alteration through STDP following subliminal stimulation may be a possible neuronal mechanism for leaving its memory trace in cortical circuitry. Regulation of local ambient GABA levels by transporter-mediated GABA import and export may be crucial for subliminal learning.
Effects of cue focality on the neural mechanisms of prospective memory: A meta-analysis of neuroimaging studies.

PubMed

Cona, Giorgia; Bisiacchi, Patrizia Silvia; Sartori, Giuseppe; Scarpazza, Cristina

2016-05-17

Remembering to execute pre-defined intentions at the appropriate time in the future is typically referred to as Prospective Memory (PM). Studies of PM showed that distinct cognitive processes underlie the execution of delayed intentions depending on whether the cue associated with such intentions is focal to ongoing activity processing or not (i.e., cue focality). The present activation likelihood estimation (ALE) meta-analysis revealed several differences in brain activity as a function of focality of the PM cue. The retrieval of intention is supported mainly by left anterior prefrontal cortex (Brodmann Area, BA 10) in nonfocal tasks, and by cerebellum and ventral parietal regions in focal tasks. Furthermore, the precuneus showed increased activation during the maintenance phase of intentions compared to the retrieval phase in nonfocal tasks, whereas the inferior parietal lobule showed increased activation during the retrieval of intention compared to maintenance phase in the focal tasks. Finally, the retrieval of intention relies more on the activity in anterior cingulate cortex for nonfocal tasks, and on posterior cingulate cortex for focal tasks. Such focality-related pattern of activations suggests that prospective remembering is mediated mainly by top-down and stimulus-independent processes in nonfocal tasks, whereas by more automatic, bottom-up, processes in focal tasks.
Effects of cue focality on the neural mechanisms of prospective memory: A meta-analysis of neuroimaging studies

PubMed Central

Cona, Giorgia; Bisiacchi, Patrizia Silvia; Sartori, Giuseppe; Scarpazza, Cristina

2016-01-01

Remembering to execute pre-defined intentions at the appropriate time in the future is typically referred to as Prospective Memory (PM). Studies of PM showed that distinct cognitive processes underlie the execution of delayed intentions depending on whether the cue associated with such intentions is focal to ongoing activity processing or not (i.e., cue focality). The present activation likelihood estimation (ALE) meta-analysis revealed several differences in brain activity as a function of focality of the PM cue. The retrieval of intention is supported mainly by left anterior prefrontal cortex (Brodmann Area, BA 10) in nonfocal tasks, and by cerebellum and ventral parietal regions in focal tasks. Furthermore, the precuneus showed increased activation during the maintenance phase of intentions compared to the retrieval phase in nonfocal tasks, whereas the inferior parietal lobule showed increased activation during the retrieval of intention compared to maintenance phase in the focal tasks. Finally, the retrieval of intention relies more on the activity in anterior cingulate cortex for nonfocal tasks, and on posterior cingulate cortex for focal tasks. Such focality-related pattern of activations suggests that prospective remembering is mediated mainly by top-down and stimulus-independent processes in nonfocal tasks, whereas by more automatic, bottom-up, processes in focal tasks. PMID:27185531
Assessing the Depth of Cognitive Processing as the Basis for Potential User-State Adaptation

PubMed Central

Nicolae, Irina-Emilia; Acqualagna, Laura; Blankertz, Benjamin

2017-01-01

Objective: Decoding neurocognitive processes on a single-trial basis with Brain-Computer Interface (BCI) techniques can reveal the user's internal interpretation of the current situation. Such information can potentially be exploited to make devices and interfaces more user aware. In this line of research, we took a further step by studying neural correlates of different levels of cognitive processes and developing a method that allows to quantify how deeply presented information is processed in the brain. Methods/Approach: Seventeen participants took part in an EEG study in which we evaluated different levels of cognitive processing (no processing, shallow, and deep processing) within three distinct domains (memory, language, and visual imagination). Our investigations showed gradual differences in the amplitudes of event-related potentials (ERPs) and in the extend and duration of event-related desynchronization (ERD) which both correlate with task difficulty. We performed multi-modal classification to map the measured correlates of neurocognitive processing to the corresponding level of processing. Results: Successful classification of the neural components was achieved, which reflects the level of cognitive processing performed by the participants. The results show performances above chance level for each participant and a mean performance of 70–90% for all conditions and classification pairs. Significance: The successful estimation of the level of cognition on a single-trial basis supports the feasibility of user-state adaptation based on ongoing neural activity. There is a variety of potential use cases such as: a user-friendly adaptive design of an interface or the development of assistance systems in safety critical workplaces. PMID:29046625
Interaction matters: A perceived social partner alters the neural processing of human speech.

PubMed

Rice, Katherine; Redcay, Elizabeth

2016-04-01

Mounting evidence suggests that social interaction changes how communicative behaviors (e.g., spoken language, gaze) are processed, but the precise neural bases by which social-interactive context may alter communication remain unknown. Various perspectives suggest that live interactions are more rewarding, more attention-grabbing, or require increased mentalizing-thinking about the thoughts of others. Dissociating between these possibilities is difficult because most extant neuroimaging paradigms examining social interaction have not directly compared live paradigms to conventional "offline" (or recorded) paradigms. We developed a novel fMRI paradigm to assess whether and how an interactive context changes the processing of speech matched in content and vocal characteristics. Participants listened to short vignettes--which contained no reference to people or mental states--believing that some vignettes were prerecorded and that others were presented over a real-time audio-feed by a live social partner. In actuality, all speech was prerecorded. Simply believing that speech was live increased activation in each participant's own mentalizing regions, defined using a functional localizer. Contrasting live to recorded speech did not reveal significant differences in attention or reward regions. Further, higher levels of autistic-like traits were associated with altered neural specialization for live interaction. These results suggest that humans engage in ongoing mentalizing about social partners, even when such mentalizing is not explicitly required, illustrating how social context shapes social cognition. Understanding communication in social context has important implications for typical and atypical social processing, especially for disorders like autism where social difficulties are more acute in live interaction. Copyright © 2015 Elsevier Inc. All rights reserved.
Dissociable identity- and modality-specific neural representations as revealed by cross-modal nonspatial inhibition of return.

PubMed

Chi, Yukai; Yue, Zhenzhu; Liu, Yupin; Mo, Lei; Chen, Qi

2014-08-01

There are ongoing debates on whether object concepts are coded as supramodal identity-based or modality-specific representations in the human brain. In this fMRI study, we adopted a cross-modal "prime-neutral cue-target" semantic priming paradigm, in which the prime-target relationship was manipulated along both the identity and the modality dimensions. The prime and the target could refer to either the same or different semantic identities, and could be delivered via either the same or different sensory modalities. By calculating the main effects and interactions of this 2 (identity cue validity: "Identity_Cued" vs. "Identity_Uncued") × 2 (modality cue validity: "Modality_Cued" vs. "Modality_Uncued") factorial design, we aimed at dissociating three neural networks involved in creating novel identity-specific representations independent of sensory modality, in creating modality-specific representations independent of semantic identity, and in evaluating changes of an object along both the identity and the modality dimensions, respectively. Our results suggested that bilateral lateral occipital cortex was involved in creating a new supramodal semantic representation irrespective of the input modality, left dorsal premotor cortex, and left intraparietal sulcus were involved in creating a new modality-specific representation irrespective of its semantic identity, and bilateral superior temporal sulcus was involved in creating a representation when the identity and modality properties were both cued or both uncued. In addition, right inferior frontal gyrus showed enhanced neural activity only when both the identity and the modality of the target were new, indicating its functional role in novelty detection. Copyright © 2014 Wiley Periodicals, Inc.
Assessing the Depth of Cognitive Processing as the Basis for Potential User-State Adaptation.

PubMed

Nicolae, Irina-Emilia; Acqualagna, Laura; Blankertz, Benjamin

2017-01-01

Objective: Decoding neurocognitive processes on a single-trial basis with Brain-Computer Interface (BCI) techniques can reveal the user's internal interpretation of the current situation. Such information can potentially be exploited to make devices and interfaces more user aware. In this line of research, we took a further step by studying neural correlates of different levels of cognitive processes and developing a method that allows to quantify how deeply presented information is processed in the brain. Methods/Approach: Seventeen participants took part in an EEG study in which we evaluated different levels of cognitive processing (no processing, shallow, and deep processing) within three distinct domains (memory, language, and visual imagination). Our investigations showed gradual differences in the amplitudes of event-related potentials (ERPs) and in the extend and duration of event-related desynchronization (ERD) which both correlate with task difficulty. We performed multi-modal classification to map the measured correlates of neurocognitive processing to the corresponding level of processing. Results: Successful classification of the neural components was achieved, which reflects the level of cognitive processing performed by the participants. The results show performances above chance level for each participant and a mean performance of 70-90% for all conditions and classification pairs. Significance: The successful estimation of the level of cognition on a single-trial basis supports the feasibility of user-state adaptation based on ongoing neural activity. There is a variety of potential use cases such as: a user-friendly adaptive design of an interface or the development of assistance systems in safety critical workplaces.
Neural crest specification and migration independently require NSD3-related lysine methyltransferase activity

PubMed Central

Jacques-Fricke, Bridget T.; Gammill, Laura S.

2014-01-01

Neural crest precursors express genes that cause them to become migratory, multipotent cells, distinguishing them from adjacent stationary neural progenitors in the neurepithelium. Histone methylation spatiotemporally regulates neural crest gene expression; however, the protein methyltransferases active in neural crest precursors are unknown. Moreover, the regulation of methylation during the dynamic process of neural crest migration is unclear. Here we show that the lysine methyltransferase NSD3 is abundantly and specifically expressed in premigratory and migratory neural crest cells. NSD3 expression commences before up-regulation of neural crest genes, and NSD3 is necessary for expression of the neural plate border gene Msx1, as well as the key neural crest transcription factors Sox10, Snail2, Sox9, and FoxD3, but not gene expression generally. Nevertheless, only Sox10 histone H3 lysine 36 dimethylation requires NSD3, revealing unexpected complexity in NSD3-dependent neural crest gene regulation. In addition, by temporally limiting expression of a dominant negative to migratory stages, we identify a novel, direct requirement for NSD3-related methyltransferase activity in neural crest migration. These results identify NSD3 as the first protein methyltransferase essential for neural crest gene expression during specification and show that NSD3-related methyltransferase activity independently regulates migration. PMID:25318671

SNW1 Is a Critical Regulator of Spatial BMP Activity, Neural Plate Border Formation, and Neural Crest Specification in Vertebrate Embryos

PubMed Central

Wu, Mary Y.; Ramel, Marie-Christine; Howell, Michael; Hill, Caroline S.

2011-01-01

Bone morphogenetic protein (BMP) gradients provide positional information to direct cell fate specification, such as patterning of the vertebrate ectoderm into neural, neural crest, and epidermal tissues, with precise borders segregating these domains. However, little is known about how BMP activity is regulated spatially and temporally during vertebrate development to contribute to embryonic patterning, and more specifically to neural crest formation. Through a large-scale in vivo functional screen in Xenopus for neural crest fate, we identified an essential regulator of BMP activity, SNW1. SNW1 is a nuclear protein known to regulate gene expression. Using antisense morpholinos to deplete SNW1 protein in both Xenopus and zebrafish embryos, we demonstrate that dorsally expressed SNW1 is required for neural crest specification, and this is independent of mesoderm formation and gastrulation morphogenetic movements. By exploiting a combination of immunostaining for phosphorylated Smad1 in Xenopus embryos and a BMP-dependent reporter transgenic zebrafish line, we show that SNW1 regulates a specific domain of BMP activity in the dorsal ectoderm at the neural plate border at post-gastrula stages. We use double in situ hybridizations and immunofluorescence to show how this domain of BMP activity is spatially positioned relative to the neural crest domain and that of SNW1 expression. Further in vivo and in vitro assays using cell culture and tissue explants allow us to conclude that SNW1 acts upstream of the BMP receptors. Finally, we show that the requirement of SNW1 for neural crest specification is through its ability to regulate BMP activity, as we demonstrate that targeted overexpression of BMP to the neural plate border is sufficient to restore neural crest formation in Xenopus SNW1 morphants. We conclude that through its ability to regulate a specific domain of BMP activity in the vertebrate embryo, SNW1 is a critical regulator of neural plate border formation and thus neural crest specification. PMID:21358802
Medical aspects of pediatric rehabilitation after moderate to severe traumatic brain injury.

PubMed

Cantore, Lisa; Norwood, Kenneth; Patrick, Peter

2012-01-01

Recovery from severe traumatic brain injury (TBI) is prolonged, complicated and challenging. Medical rehabilitation is the bridge from acute medical care and stabilization to community reintegration. The process of caring for the recovering brain introduces unknown challenges of neural plasticity with demands to restore and to also move the child and family back to the developmental trajectory they once knew. While the ongoing focus is to maintain and advance medical stability, co- morbid conditions are addressed, and a plan for ongoing health is established. While no one manuscript can cover all of the medical aspects, this article will present in a "systems review" manner the most challenging and demanding medical conditions that children may confront following severe brain injury.
Acoustic and higher-level representations of naturalistic auditory scenes in human auditory and frontal cortex.

PubMed

Hausfeld, Lars; Riecke, Lars; Formisano, Elia

2018-06-01

Often, in everyday life, we encounter auditory scenes comprising multiple simultaneous sounds and succeed to selectively attend to only one sound, typically the most relevant for ongoing behavior. Studies using basic sounds and two-talker stimuli have shown that auditory selective attention aids this by enhancing the neural representations of the attended sound in auditory cortex. It remains unknown, however, whether and how this selective attention mechanism operates on representations of auditory scenes containing natural sounds of different categories. In this high-field fMRI study we presented participants with simultaneous voices and musical instruments while manipulating their focus of attention. We found an attentional enhancement of neural sound representations in temporal cortex - as defined by spatial activation patterns - at locations that depended on the attended category (i.e., voices or instruments). In contrast, we found that in frontal cortex the site of enhancement was independent of the attended category and the same regions could flexibly represent any attended sound regardless of its category. These results are relevant to elucidate the interacting mechanisms of bottom-up and top-down processing when listening to real-life scenes comprised of multiple sound categories. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
How Early Hormones Shape Gender Development

PubMed Central

Berenbaum, Sheri A.; Beltz, Adriene M.

2015-01-01

Many important psychological characteristics show sex differences, and are influenced by sex hormones at different developmental periods. We focus on the role of sex hormones in early development, particularly the differential effects of prenatal androgens on aspects of gender development. Increasing evidence confirms that prenatal androgens have facilitative effects on male-typed activity interests and engagement (including child toy preferences and adult careers), and spatial abilities, but relatively minimal effects on gender identity. Recent emphasis has been directed to the psychological mechanisms underlying these effects (including sex differences in propulsive movement, and androgen effects on interest in people versus things), and neural substrates of androgen effects (including regional brain volumes, and neural responses to mental rotation, sexually arousing stimuli, emotion, and reward). Ongoing and planned work is focused on understanding the ways in which hormones act jointly with the social environment across time to produce varying trajectories of gender development, and clarifying mechanisms by which androgens affect behaviors. Such work will be facilitated by applying lessons from other species, and by expanding methodology. Understanding hormonal influences on gender development enhances knowledge of psychological development generally, and has important implications for basic and applied questions, including sex differences in psychopathology, women’s underrepresentation in science and math, and clinical care of individuals with variations in gender expression. PMID:26688827
Guiding the study of brain dynamics by using first-person data: Synchrony patterns correlate with ongoing conscious states during a simple visual task

PubMed Central

Lutz, Antoine; Lachaux, Jean-Philippe; Martinerie, Jacques; Varela, Francisco J.

2002-01-01

Even during well-calibrated cognitive tasks, successive brain responses to repeated identical stimulations are highly variable. The source of this variability is believed to reside mainly in fluctuations of the subject's cognitive “context” defined by his/her attentive state, spontaneous thought process, strategy to carry out the task, and so on … As these factors are hard to manipulate precisely, they are usually not controlled, and the variability is discarded by averaging techniques. We combined first-person data and the analysis of neural processes to reduce such noise. We presented the subjects with a three-dimensional illusion and recorded their electrical brain activity and their own report about their cognitive context. Trials were clustered according to these first-person data, and separate dynamical analyses were conducted for each cluster. We found that (i) characteristic patterns of endogenous synchrony appeared in frontal electrodes before stimulation. These patterns depended on the degree of preparation and the immediacy of perception as verbally reported. (ii) These patterns were stable for several recordings. (iii) Preparatory states modulate both the behavioral performance and the evoked and induced synchronous patterns that follow. (iv) These results indicated that first-person data can be used to detect and interpret neural processes. PMID:11805299
Identifying Emotions on the Basis of Neural Activation

PubMed Central

Kassam, Karim S.; Markey, Amanda R.; Cherkassky, Vladimir L.; Loewenstein, George; Just, Marcel Adam

2013-01-01

We attempt to determine the discriminability and organization of neural activation corresponding to the experience of specific emotions. Method actors were asked to self-induce nine emotional states (anger, disgust, envy, fear, happiness, lust, pride, sadness, and shame) while in an fMRI scanner. Using a Gaussian Naïve Bayes pooled variance classifier, we demonstrate the ability to identify specific emotions experienced by an individual at well over chance accuracy on the basis of: 1) neural activation of the same individual in other trials, 2) neural activation of other individuals who experienced similar trials, and 3) neural activation of the same individual to a qualitatively different type of emotion induction. Factor analysis identified valence, arousal, sociality, and lust as dimensions underlying the activation patterns. These results suggest a structure for neural representations of emotion and inform theories of emotional processing. PMID:23840392
Identifying Emotions on the Basis of Neural Activation.

PubMed

Kassam, Karim S; Markey, Amanda R; Cherkassky, Vladimir L; Loewenstein, George; Just, Marcel Adam

2013-01-01

We attempt to determine the discriminability and organization of neural activation corresponding to the experience of specific emotions. Method actors were asked to self-induce nine emotional states (anger, disgust, envy, fear, happiness, lust, pride, sadness, and shame) while in an fMRI scanner. Using a Gaussian Naïve Bayes pooled variance classifier, we demonstrate the ability to identify specific emotions experienced by an individual at well over chance accuracy on the basis of: 1) neural activation of the same individual in other trials, 2) neural activation of other individuals who experienced similar trials, and 3) neural activation of the same individual to a qualitatively different type of emotion induction. Factor analysis identified valence, arousal, sociality, and lust as dimensions underlying the activation patterns. These results suggest a structure for neural representations of emotion and inform theories of emotional processing.
Predictive Coding or Evidence Accumulation? False Inference and Neuronal Fluctuations

PubMed Central

Friston, Karl J.; Kleinschmidt, Andreas

2010-01-01

Perceptual decisions can be made when sensory input affords an inference about what generated that input. Here, we report findings from two independent perceptual experiments conducted during functional magnetic resonance imaging (fMRI) with a sparse event-related design. The first experiment, in the visual modality, involved forced-choice discrimination of coherence in random dot kinematograms that contained either subliminal or periliminal motion coherence. The second experiment, in the auditory domain, involved free response detection of (non-semantic) near-threshold acoustic stimuli. We analysed fluctuations in ongoing neural activity, as indexed by fMRI, and found that neuronal activity in sensory areas (extrastriate visual and early auditory cortex) biases perceptual decisions towards correct inference and not towards a specific percept. Hits (detection of near-threshold stimuli) were preceded by significantly higher activity than both misses of identical stimuli or false alarms, in which percepts arise in the absence of appropriate sensory input. In accord with predictive coding models and the free-energy principle, this observation suggests that cortical activity in sensory brain areas reflects the precision of prediction errors and not just the sensory evidence or prediction errors per se. PMID:20369004
Inactivity-induced respiratory plasticity: Protecting the drive to breathe in disorders that reduce respiratory neural activity☆

PubMed Central

Strey, K.A.; Baertsch, N.A.; Baker-Herman, T.L.

2013-01-01

Multiple forms of plasticity are activated following reduced respiratory neural activity. For example, in ventilated rats, a central neural apnea elicits a rebound increase in phrenic and hypoglossal burst amplitude upon resumption of respiratory neural activity, forms of plasticity called inactivity-induced phrenic and hypoglossal motor facilitation (iPMF and iHMF), respectively. Here, we provide a conceptual framework for plasticity following reduced respiratory neural activity to guide future investigations. We review mechanisms giving rise to iPMF and iHMF, present new data suggesting that inactivity-induced plasticity is observed in inspiratory intercostals (iIMF) and point out gaps in our knowledge. We then survey conditions relevant to human health characterized by reduced respiratory neural activity and discuss evidence that inactivity-induced plasticity is elicited during these conditions. Understanding the physiological impact and circumstances in which inactivity-induced respiratory plasticity is elicited may yield novel insights into the treatment of disorders characterized by reductions in respiratory neural activity. PMID:23816599
Neurosurgery and the dawning age of Brain-Machine Interfaces

PubMed Central

Rowland, Nathan C.; Breshears, Jonathan; Chang, Edward F.

2013-01-01

Brain–machine interfaces (BMIs) are on the horizon for clinical neurosurgery. Electrocorticography-based platforms are less invasive than implanted microelectrodes, however, the latter are unmatched in their ability to achieve fine motor control of a robotic prosthesis capable of natural human behaviors. These technologies will be crucial to restoring neural function to a large population of patients with severe neurologic impairment – including those with spinal cord injury, stroke, limb amputation, and disabling neuromuscular disorders such as amyotrophic lateral sclerosis. On the opposite end of the spectrum are neural enhancement technologies for specialized applications such as combat. An ongoing ethical dialogue is imminent as we prepare for BMI platforms to enter the neurosurgical realm of clinical management. PMID:23653884
Dlx proteins position the neural plate border and determine adjacent cell fates.

PubMed

Woda, Juliana M; Pastagia, Julie; Mercola, Mark; Artinger, Kristin Bruk

2003-01-01

The lateral border of the neural plate is a major source of signals that induce primary neurons, neural crest cells and cranial placodes as well as provide patterning cues to mesodermal structures such as somites and heart. Whereas secreted BMP, FGF and Wnt proteins influence the differentiation of neural and non-neural ectoderm, we show here that members of the Dlx family of transcription factors position the border between neural and non-neural ectoderm and are required for the specification of adjacent cell fates. Inhibition of endogenous Dlx activity in Xenopus embryos with an EnR-Dlx homeodomain fusion protein expands the neural plate into non-neural ectoderm tissue whereas ectopic activation of Dlx target genes inhibits neural plate differentiation. Importantly, the stereotypic pattern of border cell fates in the adjacent ectoderm is re-established only under conditions where the expanded neural plate abuts Dlx-positive non-neural ectoderm. Experiments in which presumptive neural plate was grafted to ventral ectoderm reiterate induction of neural crest and placodal lineages and also demonstrate that Dlx activity is required in non-neural ectoderm for the production of signals needed for induction of these cells. We propose that Dlx proteins regulate intercellular signaling across the interface between neural and non-neural ectoderm that is critical for inducing and patterning adjacent cell fates.
Association of Marijuana Use With Blunted Nucleus Accumbens Response to Reward Anticipation.

PubMed

Martz, Meghan E; Trucco, Elisa M; Cope, Lora M; Hardee, Jillian E; Jester, Jennifer M; Zucker, Robert A; Heitzeg, Mary M

2016-08-01

Marijuana use may alter ventral striatal response to reward, which might heighten susceptibility to substance use disorder. Longitudinal research is needed to determine the effects of marijuana use on neural function involved in reward response. To determine whether marijuana use among young adults prospectively affects nucleus accumbens (NAcc) activation during reward anticipation. One hundred eight young adults were recruited from the Michigan Longitudinal Study, an ongoing study of youth at high risk for substance use disorder and a contrast sample of control families. Participants underwent 3 consecutive functional magnetic resonance imaging scans at approximate ages of 20 (time 1), 22 (time 2), and 24 (time 3) years. Self-report data on marijuana and other drug use occasions were collected annually since age 11 years. Cross-lagged models were used to test the association of marijuana use with neural response in the NAcc to reward anticipation during a monetary incentive delay task controlling for sex, age, other substance use, and family history of substance use disorder. Of 108 participants, 39 (36.1%) were female and mean (SD) age at baseline was 20.1 (1.4) years. Greater marijuana use was associated with later blunted activation in the NAcc during reward anticipation (time 1 to time 2: β = -0.26, P = .04; time 2 to time 3: β = -0.25, P = .01). When the cross-lagged model was tested with the inclusion of previous and concurrent cigarette use, the effect of marijuana use from time 2 to time 3 remained significant (β = -0.29; P = .005) and the effect of cigarette use was nonsignificant. The findings of this study indicate that marijuana use is associated with decreased neural response in the NAcc during the anticipation of nondrug rewards. Over time, marijuana use may alter anticipatory reward processing in the NAcc, which may increase the risk for continued drug use and later addiction.
The association between brain activity and motor imagery during motor illusion induction by vibratory stimulation.

PubMed

Kodama, Takayuki; Nakano, Hideki; Katayama, Osamu; Murata, Shin

2017-01-01

The association between motor imagery ability and brain neural activity that leads to the manifestation of a motor illusion remains unclear. In this study, we examined the association between the ability to generate motor imagery and brain neural activity leading to the induction of a motor illusion by vibratory stimulation. The sample consisted of 20 healthy individuals who did not have movement or sensory disorders. We measured the time between the starting and ending points of a motor illusion (the time to illusion induction, TII) and performed electroencephalography (EEG). We conducted a temporo-spatial analysis on brain activity leading to the induction of motor illusions using the EEG microstate segmentation method. Additionally, we assessed the ability to generate motor imagery using the Japanese version of the Movement Imagery Questionnaire-Revised (JMIQ-R) prior to performing the task and examined the associations among brain neural activity levels as identified by microstate segmentation method, TII, and the JMIQ-R scores. The results showed four typical microstates during TII and significantly higher neural activity in the ventrolateral prefrontal cortex, primary sensorimotor area, supplementary motor area (SMA), and inferior parietal lobule (IPL). Moreover, there were significant negative correlations between the neural activity of the primary motor cortex (MI), SMA, IPL, and TII, and a significant positive correlation between the neural activity of the SMA and the JMIQ-R scores. These findings suggest the possibility that a neural network primarily comprised of the neural activity of SMA and M1, which are involved in generating motor imagery, may be the neural basis for inducing motor illusions. This may aid in creating a new approach to neurorehabilitation that enables a more robust reorganization of the neural base for patients with brain dysfunction with a motor function disorder.
Neural reactivation links unconscious thought to decision-making performance.

PubMed

Creswell, John David; Bursley, James K; Satpute, Ajay B

2013-12-01

Brief periods of unconscious thought (UT) have been shown to improve decision making compared with making an immediate decision (ID). We reveal a neural mechanism for UT in decision making using blood oxygen level-dependent (BOLD) functional magnetic resonance imaging. Participants (N = 33) encoded information on a set of consumer products (e.g. 48 attributes describing four different cars), and we manipulated whether participants (i) consciously thought about this information (conscious thought), (ii) completed a difficult 2-back working memory task (UT) or (iii) made an immediate decision about the consumer products (ID) in a within-subjects blocked design. To differentiate UT neural activity from 2-back working memory neural activity, participants completed an independent 2-back task and this neural activity was subtracted from neural activity occurring during the UT 2-back task. Consistent with a neural reactivation account, we found that the same regions activated during the encoding of complex decision information (right dorsolateral prefrontal cortex and left intermediate visual cortex) continued to be activated during a subsequent 2-min UT period. Moreover, neural reactivation in these regions was predictive of subsequent behavioral decision-making performance after the UT period. These results provide initial evidence for post-encoding unconscious neural reactivation in facilitating decision making.
Neural Categorization of Vibrotactile Frequency in Flutter and Vibration Stimulations: An fMRI Study.

PubMed

Kim, Junsuk; Chung, Yoon Gi; Chung, Soon-Cheol; Bulthoff, Heinrich H; Kim, Sung-Phil

2016-01-01

As the use of wearable haptic devices with vibrating alert features is commonplace, an understanding of the perceptual categorization of vibrotactile frequencies has become important. This understanding can be substantially enhanced by unveiling how neural activity represents vibrotactile frequency information. Using functional magnetic resonance imaging (fMRI), this study investigated categorical clustering patterns of the frequency-dependent neural activity evoked by vibrotactile stimuli with gradually changing frequencies from 20 to 200 Hz. First, a searchlight multi-voxel pattern analysis (MVPA) was used to find brain regions exhibiting neural activities associated with frequency information. We found that the contralateral postcentral gyrus (S1) and the supramarginal gyrus (SMG) carried frequency-dependent information. Next, we applied multidimensional scaling (MDS) to find low-dimensional neural representations of different frequencies obtained from the multi-voxel activity patterns within these regions. The clustering analysis on the MDS results showed that neural activity patterns of 20-100 Hz and 120-200 Hz were divided into two distinct groups. Interestingly, this neural grouping conformed to the perceptual frequency categories found in the previous behavioral studies. Our findings therefore suggest that neural activity patterns in the somatosensory cortical regions may provide a neural basis for the perceptual categorization of vibrotactile frequency.
Neural reactivation links unconscious thought to decision-making performance

PubMed Central

Bursley, James K.; Satpute, Ajay B.

2013-01-01

Brief periods of unconscious thought (UT) have been shown to improve decision making compared with making an immediate decision (ID). We reveal a neural mechanism for UT in decision making using blood oxygen level-dependent (BOLD) functional magnetic resonance imaging. Participants (N = 33) encoded information on a set of consumer products (e.g. 48 attributes describing four different cars), and we manipulated whether participants (i) consciously thought about this information (conscious thought), (ii) completed a difficult 2-back working memory task (UT) or (iii) made an immediate decision about the consumer products (ID) in a within-subjects blocked design. To differentiate UT neural activity from 2-back working memory neural activity, participants completed an independent 2-back task and this neural activity was subtracted from neural activity occurring during the UT 2-back task. Consistent with a neural reactivation account, we found that the same regions activated during the encoding of complex decision information (right dorsolateral prefrontal cortex and left intermediate visual cortex) continued to be activated during a subsequent 2-min UT period. Moreover, neural reactivation in these regions was predictive of subsequent behavioral decision-making performance after the UT period. These results provide initial evidence for post-encoding unconscious neural reactivation in facilitating decision making. PMID:23314012
Distributed task-specific processing of somatosensory feedback for voluntary motor control

PubMed Central

Omrani, Mohsen; Murnaghan, Chantelle D; Pruszynski, J Andrew; Scott, Stephen H

2016-01-01

Corrective responses to limb disturbances are surprisingly complex, but the neural basis of these goal-directed responses is poorly understood. Here we show that somatosensory feedback is transmitted to many sensory and motor cortical regions within 25 ms of a mechanical disturbance applied to the monkey’s arm. When limb feedback was salient to an ongoing motor action (task engagement), neurons in parietal area 5 immediately (~25 ms) increased their response to limb disturbances, whereas neurons in other regions did not alter their response until 15 to 40 ms later. In contrast, initiation of a motor action elicited by a limb disturbance (target selection) altered neural responses in primary motor cortex ~65 ms after the limb disturbance, and then in dorsal premotor cortex, with no effect in parietal regions until 150 ms post-perturbation. Our findings highlight broad parietofrontal circuits that provide the neural substrate for goal-directed corrections, an essential aspect of highly skilled motor behaviors. DOI: http://dx.doi.org/10.7554/eLife.13141.001 PMID:27077949
The application of hybrid artificial intelligence systems for forecasting

NASA Astrophysics Data System (ADS)

Lees, Brian; Corchado, Juan

1999-03-01

The results to date are presented from an ongoing investigation, in which the aim is to combine the strengths of different artificial intelligence methods into a single problem solving system. The premise underlying this research is that a system which embodies several cooperating problem solving methods will be capable of achieving better performance than if only a single method were employed. The work has so far concentrated on the combination of case-based reasoning and artificial neural networks. The relative merits of artificial neural networks and case-based reasoning problem solving paradigms, and their combination are discussed. The integration of these two AI problem solving methods in a hybrid systems architecture, such that the neural network provides support for learning from past experience in the case-based reasoning cycle, is then presented. The approach has been applied to the task of forecasting the variation of physical parameters of the ocean. Results obtained so far from tests carried out in the dynamic oceanic environment are presented.
The implications of brain connectivity in the neuropsychology of autism

PubMed Central

Maximo, Jose O.; Cadena, Elyse J.; Kana, Rajesh K.

2014-01-01

Autism is a neurodevelopmental disorder that has been associated with atypical brain functioning. Functional connectivity MRI (fcMRI) studies examining neural networks in autism have seen an exponential rise over the last decade. Such investigations have led to characterization of autism as a distributed neural systems disorder. Studies have found widespread cortical underconnectivity, local overconnectivity, and mixed results suggesting disrupted brain connectivity as a potential neural signature of autism. In this review, we summarize the findings of previous fcMRI studies in autism with a detailed examination of their methodology, in order to better understand its potential and to delineate the pitfalls. We also address how a multimodal neuroimaging approach (incorporating different measures of brain connectivity) may help characterize the complex neurobiology of autism at a global level. Finally, we also address the potential of neuroimaging-based markers in assisting neuropsychological assessment of autism. The quest for a biomarker for autism is still ongoing, yet new findings suggest that aberrant brain connectivity may be a promising candidate. PMID:24496901
A Higher-Order Neural Network Design for Improving Segmentation Performance in Medical Image Series

NASA Astrophysics Data System (ADS)

Selvi, Eşref; Selver, M. Alper; Güzeliş, Cüneyt; Dicle, Oǧuz

2014-03-01

Segmentation of anatomical structures from medical image series is an ongoing field of research. Although, organs of interest are three-dimensional in nature, slice-by-slice approaches are widely used in clinical applications because of their ease of integration with the current manual segmentation scheme. To be able to use slice-by-slice techniques effectively, adjacent slice information, which represents likelihood of a region to be the structure of interest, plays critical role. Recent studies focus on using distance transform directly as a feature or to increase the feature values at the vicinity of the search area. This study presents a novel approach by constructing a higher order neural network, the input layer of which receives features together with their multiplications with the distance transform. This allows higher-order interactions between features through the non-linearity introduced by the multiplication. The application of the proposed method to 9 CT datasets for segmentation of the liver shows higher performance than well-known higher order classification neural networks.

Neural decoding of collective wisdom with multi-brain computing.

PubMed

Eckstein, Miguel P; Das, Koel; Pham, Binh T; Peterson, Matthew F; Abbey, Craig K; Sy, Jocelyn L; Giesbrecht, Barry

2012-01-02

Group decisions and even aggregation of multiple opinions lead to greater decision accuracy, a phenomenon known as collective wisdom. Little is known about the neural basis of collective wisdom and whether its benefits arise in late decision stages or in early sensory coding. Here, we use electroencephalography and multi-brain computing with twenty humans making perceptual decisions to show that combining neural activity across brains increases decision accuracy paralleling the improvements shown by aggregating the observers' opinions. Although the largest gains result from an optimal linear combination of neural decision variables across brains, a simpler neural majority decision rule, ubiquitous in human behavior, results in substantial benefits. In contrast, an extreme neural response rule, akin to a group following the most extreme opinion, results in the least improvement with group size. Analyses controlling for number of electrodes and time-points while increasing number of brains demonstrate unique benefits arising from integrating neural activity across different brains. The benefits of multi-brain integration are present in neural activity as early as 200 ms after stimulus presentation in lateral occipital sites and no additional benefits arise in decision related neural activity. Sensory-related neural activity can predict collective choices reached by aggregating individual opinions, voting results, and decision confidence as accurately as neural activity related to decision components. Estimation of the potential for the collective to execute fast decisions by combining information across numerous brains, a strategy prevalent in many animals, shows large time-savings. Together, the findings suggest that for perceptual decisions the neural activity supporting collective wisdom and decisions arises in early sensory stages and that many properties of collective cognition are explainable by the neural coding of information across multiple brains. Finally, our methods highlight the potential of multi-brain computing as a technique to rapidly and in parallel gather increased information about the environment as well as to access collective perceptual/cognitive choices and mental states. Copyright © 2011 Elsevier Inc. All rights reserved.
Neural dynamics during repetitive visual stimulation

NASA Astrophysics Data System (ADS)

Tsoneva, Tsvetomira; Garcia-Molina, Gary; Desain, Peter

2015-12-01

Objective. Steady-state visual evoked potentials (SSVEPs), the brain responses to repetitive visual stimulation (RVS), are widely utilized in neuroscience. Their high signal-to-noise ratio and ability to entrain oscillatory brain activity are beneficial for their applications in brain-computer interfaces, investigation of neural processes underlying brain rhythmic activity (steady-state topography) and probing the causal role of brain rhythms in cognition and emotion. This paper aims at analyzing the space and time EEG dynamics in response to RVS at the frequency of stimulation and ongoing rhythms in the delta, theta, alpha, beta, and gamma bands. Approach.We used electroencephalography (EEG) to study the oscillatory brain dynamics during RVS at 10 frequencies in the gamma band (40-60 Hz). We collected an extensive EEG data set from 32 participants and analyzed the RVS evoked and induced responses in the time-frequency domain. Main results. Stable SSVEP over parieto-occipital sites was observed at each of the fundamental frequencies and their harmonics and sub-harmonics. Both the strength and the spatial propagation of the SSVEP response seem sensitive to stimulus frequency. The SSVEP was more localized around the parieto-occipital sites for higher frequencies (>54 Hz) and spread to fronto-central locations for lower frequencies. We observed a strong negative correlation between stimulation frequency and relative power change at that frequency, the first harmonic and the sub-harmonic components over occipital sites. Interestingly, over parietal sites for sub-harmonics a positive correlation of relative power change and stimulation frequency was found. A number of distinct patterns in delta (1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz) and beta (15-30 Hz) bands were also observed. The transient response, from 0 to about 300 ms after stimulation onset, was accompanied by increase in delta and theta power over fronto-central and occipital sites, which returned to baseline after approx. 500 ms. During the steady-state response, we observed alpha band desynchronization over occipital sites and after 500 ms also over frontal sites, while neighboring areas synchronized. The power in beta band over occipital sites increased during the stimulation period, possibly caused by increase in power at sub-harmonic frequencies of stimulation. Gamma power was also enhanced by the stimulation. Significance. These findings have direct implications on the use of RVS and SSVEPs for neural process investigation through steady-state topography, controlled entrainment of brain oscillations and BCIs. A deep understanding of SSVEP propagation in time and space and the link with ongoing brain rhythms is crucial for optimizing the typical SSVEP applications for studying, assisting, or augmenting human cognitive and sensorimotor function.
Simultaneous surface and depth neural activity recording with graphene transistor-based dual-modality probes.

PubMed

Du, Mingde; Xu, Xianchen; Yang, Long; Guo, Yichuan; Guan, Shouliang; Shi, Jidong; Wang, Jinfen; Fang, Ying

2018-05-15

Subdural surface and penetrating depth probes are widely applied to record neural activities from the cortical surface and intracortical locations of the brain, respectively. Simultaneous surface and depth neural activity recording is essential to understand the linkage between the two modalities. Here, we develop flexible dual-modality neural probes based on graphene transistors. The neural probes exhibit stable electrical performance even under 90° bending because of the excellent mechanical properties of graphene, and thus allow multi-site recording from the subdural surface of rat cortex. In addition, finite element analysis was carried out to investigate the mechanical interactions between probe and cortex tissue during intracortical implantation. Based on the simulation results, a sharp tip angle of π/6 was chosen to facilitate tissue penetration of the neural probes. Accordingly, the graphene transistor-based dual-modality neural probes have been successfully applied for simultaneous surface and depth recording of epileptiform activity of rat brain in vivo. Our results show that graphene transistor-based dual-modality neural probes can serve as a facile and versatile tool to study tempo-spatial patterns of neural activities. Copyright © 2018 Elsevier B.V. All rights reserved.
How to include the variability of TMS responses in simulations: a speech mapping case study

NASA Astrophysics Data System (ADS)

De Geeter, N.; Lioumis, P.; Laakso, A.; Crevecoeur, G.; Dupré, L.

2016-11-01

When delivered over a specific cortical site, TMS can temporarily disrupt the ongoing process in that area. This allows mapping of speech-related areas for preoperative evaluation purposes. We numerically explore the observed variability of TMS responses during a speech mapping experiment performed with a neuronavigation system. We selected four cases with very small perturbations in coil position and orientation. In one case (E) a naming error occurred, while in the other cases (NEA, B, C) the subject appointed the images as smoothly as without TMS. A realistic anisotropic head model was constructed of the subject from T1-weighted and diffusion-weighted MRI. The induced electric field distributions were computed, associated to the coil parameters retrieved from the neuronavigation system. Finally, the membrane potentials along relevant white matter fibre tracts, extracted from DTI-based tractography, were computed using a compartmental cable equation. While only minor differences could be noticed between the induced electric field distributions of the four cases, computing the corresponding membrane potentials revealed different subsets of tracts were activated. A single tract was activated for all coil positions. Another tract was only triggered for case E. NEA induced action potentials in 13 tracts, while NEB stimulated 11 tracts and NEC one. The calculated results are certainly sensitive to the coil specifications, demonstrating the observed variability in this study. However, even though a tract connecting Broca’s with Wernicke’s area is only triggered for the error case, further research is needed on other study cases and on refining the neural model with synapses and network connections. Case- and subject-specific modelling that includes both electromagnetic fields and neuronal activity enables demonstration of the variability in TMS experiments and can capture the interaction with complex neural networks.
Vertex Stimulation as a Control Site for Transcranial Magnetic Stimulation: A Concurrent TMS/fMRI Study.

PubMed

Jung, JeYoung; Bungert, Andreas; Bowtell, Richard; Jackson, Stephen R

2016-01-01

A common control condition for transcranial magnetic stimulation (TMS) studies is to apply stimulation at the vertex. An assumption of vertex stimulation is that it has relatively little influence over on-going brain processes involved in most experimental tasks, however there has been little attempt to measure neural changes linked to vertex TMS. Here we directly test this assumption by using a concurrent TMS/fMRI paradigm in which we investigate fMRI blood-oxygenation-level-dependent (BOLD) signal changes across the whole brain linked to vertex stimulation. Thirty-two healthy participants to part in this study. Twenty-one were stimulated at the vertex, at 120% of resting motor threshold (RMT), with short bursts of 1 Hz TMS, while functional magnetic resonance imaging (fMRI) BOLD images were acquired. As a control condition, we delivered TMS pulses over the left primary motor cortex using identical parameters to 11 other participants. Vertex stimulation did not evoke increased BOLD activation at the stimulated site. By contrast we observed widespread BOLD deactivations across the brain, including regions within the default mode network (DMN). To examine the effects of vertex stimulation a functional connectivity analysis was conducted. The results demonstrated that stimulating the vertex with suprathreshold TMS reduced neural activity in brain regions related to the DMN but did not influence the functional connectivity of this network. Our findings provide brain imaging evidence in support of the use of vertex simulation as a control condition in TMS but confirm that vertex TMS induces regional widespread decreases in BOLD activation. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
Linking structure and activity in nonlinear spiking networks

PubMed Central

Josić, Krešimir; Shea-Brown, Eric

2017-01-01

Recent experimental advances are producing an avalanche of data on both neural connectivity and neural activity. To take full advantage of these two emerging datasets we need a framework that links them, revealing how collective neural activity arises from the structure of neural connectivity and intrinsic neural dynamics. This problem of structure-driven activity has drawn major interest in computational neuroscience. Existing methods for relating activity and architecture in spiking networks rely on linearizing activity around a central operating point and thus fail to capture the nonlinear responses of individual neurons that are the hallmark of neural information processing. Here, we overcome this limitation and present a new relationship between connectivity and activity in networks of nonlinear spiking neurons by developing a diagrammatic fluctuation expansion based on statistical field theory. We explicitly show how recurrent network structure produces pairwise and higher-order correlated activity, and how nonlinearities impact the networks’ spiking activity. Our findings open new avenues to investigating how single-neuron nonlinearities—including those of different cell types—combine with connectivity to shape population activity and function. PMID:28644840
Principles of auditory processing differ between sensory and premotor structures of the songbird forebrain

PubMed Central

Vicario, David S.

2017-01-01

Sensory and motor brain structures work in collaboration during perception. To evaluate their respective contributions, the present study recorded neural responses to auditory stimulation at multiple sites simultaneously in both the higher-order auditory area NCM and the premotor area HVC of the songbird brain in awake zebra finches (Taeniopygia guttata). Bird’s own song (BOS) and various conspecific songs (CON) were presented in both blocked and shuffled sequences. Neural responses showed plasticity in the form of stimulus-specific adaptation, with markedly different dynamics between the two structures. In NCM, the response decrease with repetition of each stimulus was gradual and long-lasting and did not differ between the stimuli or the stimulus presentation sequences. In contrast, HVC responses to CON stimuli decreased much more rapidly in the blocked than in the shuffled sequence. Furthermore, this decrease was more transient in HVC than in NCM, as shown by differential dynamics in the shuffled sequence. Responses to BOS in HVC decreased more gradually than to CON stimuli. The quality of neural representations, computed as the mutual information between stimuli and neural activity, was higher in NCM than in HVC. Conversely, internal functional correlations, estimated as the coherence between recording sites, were greater in HVC than in NCM. The cross-coherence between the two structures was weak and limited to low frequencies. These findings suggest that auditory communication signals are processed according to very different but complementary principles in NCM and HVC, a contrast that may inform study of the auditory and motor pathways for human speech processing. NEW & NOTEWORTHY Neural responses to auditory stimulation in sensory area NCM and premotor area HVC of the songbird forebrain show plasticity in the form of stimulus-specific adaptation with markedly different dynamics. These two structures also differ in stimulus representations and internal functional correlations. Accordingly, NCM seems to process the individually specific complex vocalizations of others based on prior familiarity, while HVC responses appear to be modulated by transitions and/or timing in the ongoing sequence of sounds. PMID:28031398
A wideband dual-antenna receiver for wireless recording from animals behaving in large arenas.

PubMed

Lee, Seung Bae; Yin, Ming; Manns, Joseph R; Ghovanloo, Maysam

2013-07-01

A low-noise wideband receiver (Rx) is presented for a multichannel wireless implantable neural recording (WINeR) system that utilizes time-division multiplexing of pulse width modulated (PWM) samples. The WINeR-6 Rx consists of four parts: 1) RF front end; 2) signal conditioning; 3) analog output (AO); and 4) field-programmable gate array (FPGA) back end. The RF front end receives RF-modulated neural signals in the 403-490 MHz band with a wide bandwidth of 18 MHz. The frequency-shift keying (FSK) PWM demodulator in the FPGA is a time-to-digital converter with 304 ps resolution, which converts the analog pulse width information to 16-bit digital samples. Automated frequency tracking has been implemented in the Rx to lock onto the free-running voltage-controlled oscillator in the transmitter (Tx). Two antennas and two parallel RF paths are used to increase the wireless coverage area. BCI-2000 graphical user interface has been adopted and modified to acquire, visualize, and record the recovered neural signals in real time. The AO module picks three demultiplexed channels and converts them into analog signals for direct observation on an oscilloscope. One of these signals is further amplified to generate an audio output, offering users the ability to listen to ongoing neural activity. Bench-top testing of the Rx performance with a 32-channel WINeR-6 Tx showed that the input referred noise of the entire system at a Tx-Rx distance of 1.5 m was 4.58 μV rms with 8-bit resolution at 640 kSps. In an in vivo experiment, location-specific receptive fields of hippocampal place cells were mapped during a behavioral experiment in which a rat completed 40 laps in a large circular track. Results were compared against those acquired from the same animal and the same set of electrodes by a commercial hardwired recording system to validate the wirelessly recorded signals.
A Wideband Dual-Antenna Receiver for Wireless Recording From Animals Behaving in Large Arenas

PubMed Central

Lee, Seung Bae; Yin, Ming; Manns, Joseph R.

2014-01-01

A low-noise wideband receiver (Rx) is presented for a multichannel wireless implantable neural recording (WINeR) system that utilizes time-division multiplexing of pulse width modulated (PWM) samples. The WINeR-6 Rx consists of four parts: 1) RF front end; 2) signal conditioning; 3) analog output (AO); and 4) field-programmable gate array (FPGA) back end. The RF front end receives RF-modulated neural signals in the 403–490 MHz band with a wide bandwidth of 18 MHz. The frequency-shift keying (FSK) PWM demodulator in the FPGA is a time-to-digital converter with 304 ps resolution, which converts the analog pulse width information to 16-bit digital samples. Automated frequency tracking has been implemented in the Rx to lock onto the free-running voltage-controlled oscillator in the transmitter (Tx). Two antennas and two parallel RF paths are used to increase the wireless coverage area. BCI-2000 graphical user interface has been adopted and modified to acquire, visualize, and record the recovered neural signals in real time. The AO module picks three demultiplexed channels and converts them into analog signals for direct observation on an oscilloscope. One of these signals is further amplified to generate an audio output, offering users the ability to listen to ongoing neural activity. Bench-top testing of the Rx performance with a 32-channel WINeR-6 Tx showed that the input referred noise of the entire system at a Tx–Rx distance of 1.5 m was 4.58 μVrms with 8-bit resolution at 640 kSps. In an in vivo experiment, location-specific receptive fields of hippocampal place cells were mapped during a behavioral experiment in which a rat completed 40 laps in a large circular track. Results were compared against those acquired from the same animal and the same set of electrodes by a commercial hardwired recording system to validate the wirelessly recorded signals. PMID:23428612
Dlx proteins position the neural plate border and determine adjacent cell fates

PubMed Central

Woda, Juliana M.; Pastagia, Julie; Mercola, Mark; Artinger, Kristin Bruk

2014-01-01

Summary The lateral border of the neural plate is a major source of signals that induce primary neurons, neural crest cells and cranial placodes as well as provide patterning cues to mesodermal structures such as somites and heart. Whereas secreted BMP, FGF and Wnt proteins influence the differentiation of neural and non-neural ectoderm, we show here that members of the Dlx family of transcription factors position the border between neural and non-neural ectoderm and are required for the specification of adjacent cell fates. Inhibition of endogenous Dlx activity in Xenopus embryos with an EnR-Dlx homeodomain fusion protein expands the neural plate into non-neural ectoderm tissue whereas ectopic activation of Dlx target genes inhibits neural plate differentiation. Importantly, the stereotypic pattern of border cell fates in the adjacent ectoderm is re-established only under conditions where the expanded neural plate abuts Dlx-positive non-neural ectoderm. Experiments in which presumptive neural plate was grafted to ventral ectoderm reiterate induction of neural crest and placodal lineages and also demonstrate that Dlx activity is required in non-neural ectoderm for the production of signals needed for induction of these cells. We propose that Dlx proteins regulate intercellular signaling across the interface between neural and non-neural ectoderm that is critical for inducing and patterning adjacent cell fates. PMID:12466200
Neural Oscillations Carry Speech Rhythm through to Comprehension

PubMed Central

Peelle, Jonathan E.; Davis, Matthew H.

2012-01-01

A key feature of speech is the quasi-regular rhythmic information contained in its slow amplitude modulations. In this article we review the information conveyed by speech rhythm, and the role of ongoing brain oscillations in listeners’ processing of this content. Our starting point is the fact that speech is inherently temporal, and that rhythmic information conveyed by the amplitude envelope contains important markers for place and manner of articulation, segmental information, and speech rate. Behavioral studies demonstrate that amplitude envelope information is relied upon by listeners and plays a key role in speech intelligibility. Extending behavioral findings, data from neuroimaging – particularly electroencephalography (EEG) and magnetoencephalography (MEG) – point to phase locking by ongoing cortical oscillations to low-frequency information (~4–8 Hz) in the speech envelope. This phase modulation effectively encodes a prediction of when important events (such as stressed syllables) are likely to occur, and acts to increase sensitivity to these relevant acoustic cues. We suggest a framework through which such neural entrainment to speech rhythm can explain effects of speech rate on word and segment perception (i.e., that the perception of phonemes and words in connected speech is influenced by preceding speech rate). Neuroanatomically, acoustic amplitude modulations are processed largely bilaterally in auditory cortex, with intelligible speech resulting in differential recruitment of left-hemisphere regions. Notable among these is lateral anterior temporal cortex, which we propose functions in a domain-general fashion to support ongoing memory and integration of meaningful input. Together, the reviewed evidence suggests that low-frequency oscillations in the acoustic speech signal form the foundation of a rhythmic hierarchy supporting spoken language, mirrored by phase-locked oscillations in the human brain. PMID:22973251
Optical Neural Interfaces

PubMed Central

Warden, Melissa R.; Cardin, Jessica A.; Deisseroth, Karl

2014-01-01

Genetically encoded optical actuators and indicators have changed the landscape of neuroscience, enabling targetable control and readout of specific components of intact neural circuits in behaving animals. Here, we review the development of optical neural interfaces, focusing on hardware designed for optical control of neural activity, integrated optical control and electrical readout, and optical readout of population and single-cell neural activity in freely moving mammals. PMID:25014785
Task-Dependent Changes in Cross-Level Coupling between Single Neurons and Oscillatory Activity in Multiscale Networks

PubMed Central

Canolty, Ryan T.; Ganguly, Karunesh; Carmena, Jose M.

2012-01-01

Understanding the principles governing the dynamic coordination of functional brain networks remains an important unmet goal within neuroscience. How do distributed ensembles of neurons transiently coordinate their activity across a variety of spatial and temporal scales? While a complete mechanistic account of this process remains elusive, evidence suggests that neuronal oscillations may play a key role in this process, with different rhythms influencing both local computation and long-range communication. To investigate this question, we recorded multiple single unit and local field potential (LFP) activity from microelectrode arrays implanted bilaterally in macaque motor areas. Monkeys performed a delayed center-out reach task either manually using their natural arm (Manual Control, MC) or under direct neural control through a brain-machine interface (Brain Control, BC). In accord with prior work, we found that the spiking activity of individual neurons is coupled to multiple aspects of the ongoing motor beta rhythm (10–45 Hz) during both MC and BC, with neurons exhibiting a diversity of coupling preferences. However, here we show that for identified single neurons, this beta-to-rate mapping can change in a reversible and task-dependent way. For example, as beta power increases, a given neuron may increase spiking during MC but decrease spiking during BC, or exhibit a reversible shift in the preferred phase of firing. The within-task stability of coupling, combined with the reversible cross-task changes in coupling, suggest that task-dependent changes in the beta-to-rate mapping play a role in the transient functional reorganization of neural ensembles. We characterize the range of task-dependent changes in the mapping from beta amplitude, phase, and inter-hemispheric phase differences to the spike rates of an ensemble of simultaneously-recorded neurons, and discuss the potential implications that dynamic remapping from oscillatory activity to spike rate and timing may hold for models of computation and communication in distributed functional brain networks. PMID:23284276
Social gating of sensory information during ongoing communication.

PubMed

Anders, Silke; Heussen, Yana; Sprenger, Andreas; Haynes, John-Dylan; Ethofer, Thomas

2015-01-01

Social context plays an important role in human communication. Depending on the nature of the source, the same communication signal might be processed in fundamentally different ways. However, the selective modulation (or "gating") of the flow of neural information during communication is not fully understood. Here, we use multivoxel pattern analysis (MVPA) and multivoxel connectivity analysis (MVCA), a novel technique that allows to analyse context-dependent changes of the strength interregional coupling between ensembles of voxels, to examine how the human brain differentially gates content-specific sensory information during ongoing perception of communication signals. In a simulated electronic communication experiment, participants received two alternative text messages during fMRI ("happy" or "sad") which they believed had been sent either by their real-life friend outside the scanner or by a computer. A region in the dorsal medial prefrontal cortex (dmPFC) selectively increased its functional coupling with sensory-content encoding regions in the visual cortex when a text message was perceived as being sent by the participant's friend, and decreased its functional coupling with these regions when a text message was perceived as being sent by the computer. Furthermore, the strength of neural encoding of content-specific information of text messages in the dmPFC was modulated by the social tie between the participant and her friend: the more of her spare time a participant reported to spend with her friend the stronger was the neural encoding. This suggests that the human brain selectively gates sensory information into the relevant network for processing the mental states of others, depending on the source of the communication signal. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
Stochastic inference with spiking neurons in the high-conductance state

NASA Astrophysics Data System (ADS)

Petrovici, Mihai A.; Bill, Johannes; Bytschok, Ilja; Schemmel, Johannes; Meier, Karlheinz

2016-10-01

The highly variable dynamics of neocortical circuits observed in vivo have been hypothesized to represent a signature of ongoing stochastic inference but stand in apparent contrast to the deterministic response of neurons measured in vitro. Based on a propagation of the membrane autocorrelation across spike bursts, we provide an analytical derivation of the neural activation function that holds for a large parameter space, including the high-conductance state. On this basis, we show how an ensemble of leaky integrate-and-fire neurons with conductance-based synapses embedded in a spiking environment can attain the correct firing statistics for sampling from a well-defined target distribution. For recurrent networks, we examine convergence toward stationarity in computer simulations and demonstrate sample-based Bayesian inference in a mixed graphical model. This points to a new computational role of high-conductance states and establishes a rigorous link between deterministic neuron models and functional stochastic dynamics on the network level.
Time course of ongoing activity during neuritis and following axonal transport disruption.

PubMed

Satkeviciute, Ieva; Goodwin, George; Bove, Geoffrey M; Dilley, Andrew

2018-05-01

Local nerve inflammation (neuritis) leads to ongoing activity and axonal mechanical sensitivity (AMS) along intact nociceptor axons and disrupts axonal transport. This phenomenon forms the most feasible cause of radiating pain, such as sciatica. We have previously shown that axonal transport disruption without inflammation or degeneration also leads to AMS but does not cause ongoing activity at the time point when AMS occurs, despite causing cutaneous hypersensitivity. However, there have been no systematic studies of ongoing activity during neuritis or noninflammatory axonal transport disruption. In this study, we present the time course of ongoing activity from primary sensory neurons following neuritis and vinblastine-induced axonal transport disruption. Whereas 24% of C/slow Aδ-fiber neurons had ongoing activity during neuritis, few (<10%) A- and C-fiber neurons showed ongoing activity 1-15 days following vinblastine treatment. In contrast, AMS increased transiently at the vinblastine treatment site, peaking on days 4-5 (28% of C/slow Aδ-fiber neurons) and resolved by day 15. Conduction velocities were slowed in all groups. In summary, the disruption of axonal transport without inflammation does not lead to ongoing activity in sensory neurons, including nociceptors, but does cause a rapid and transient development of AMS. Because it is proposed that AMS underlies mechanically induced radiating pain, and a transient disruption of axonal transport (as previously reported) leads to transient AMS, it follows that processes that disrupt axonal transport, such as neuritis, must persist to maintain AMS and the associated symptoms. NEW & NOTEWORTHY Many patients with radiating pain lack signs of nerve injury on clinical examination but may have neuritis, which disrupts axonal transport. We have shown that axonal transport disruption does not induce ongoing activity in primary sensory neurons but does cause transient axonal mechanical sensitivity. The present data complete a profile of key axonal sensitivities following axonal transport disruption. Collectively, this profile supports that an active peripheral process is necessary for maintained axonal sensitivities.
Neural Entrainment to Polyrhythms: A Comparison of Musicians and Non-musicians.

PubMed

Stupacher, Jan; Wood, Guilherme; Witte, Matthias

2017-01-01

Music can be thought of as a dynamic path over time. In most cases, the rhythmic structure of this path, such as specific sequences of strong and weak beats or recurring patterns, allows us to predict what and particularly when sounds are going to happen. Without this ability we would not be able to entrain body movements to music, like we do when we dance. By combining EEG and behavioral measures, the current study provides evidence illustrating the importance of ongoing neural oscillations at beat-related frequencies-i.e., neural entrainment-for tracking and predicting musical rhythms. Participants (13 musicians and 13 non-musicians) listened to drum rhythms that switched from a quadruple rhythm to a 3-over-4 polyrhythm. After a silent period of ~2-3 s, participants had to decide whether a target stimulus was presented on time with the triple beat of the polyrhythm, too early, or too late. Results showed that neural oscillations reflected the rhythmic structure of both the simple quadruple rhythm and the more complex polyrhythm with no differences between musicians and non-musicians. During silent periods, the observation of time-frequency plots and more commonly used frequency spectra analyses suggest that beat-related neural oscillations were more pronounced in musicians compared to non-musicians. Neural oscillations during silent periods are not driven by an external input and therefore are thought to reflect top-down controlled endogenous neural entrainment. The functional relevance of endogenous neural entrainment was demonstrated by a positive correlation between the amplitude of task-relevant neural oscillations during silent periods and the number of correctly identified target stimuli. In sum, our findings add to the evidence supporting the neural resonance theory of pulse and meter. Furthermore, they indicate that beat-related top-down controlled neural oscillations can exist without external stimulation and suggest that those endogenous oscillations are strengthened by musical expertise. Finally, this study shows that the analysis of neural oscillations can be a useful tool to assess how we perceive and process complex auditory stimuli such as polyrhythms.
Singing-Related Activity in Anterior Forebrain of Male Zebra Finches Reflects Courtship Motivation for Target Females

PubMed Central

Iwasaki, Mai; Poulsen, Thomas M.; Oka, Kotaro; Hessler, Neal A.

2013-01-01

A critical function of singing by male songbirds is to attract a female mate. Previous studies have suggested that the anterior forebrain system is involved in this courtship behavior. Neural activity in this system, including the striatal Area X, is strikingly dependent on the function of male singing. When males sing to attract a female bird rather than while alone, less variable neural activity results in less variable song spectral features, which may be attractive to the female. These characteristics of neural activity and singing thus may reflect a male's motivation for courtship. Here, we compared the variability of neural activity and song features between courtship singing directed to a female with whom a male had previously formed a pair-bond or to other females. Surprisingly, across all units, there was no clear tendency for a difference in variability of neural activity or song features between courtship of paired females, nonpaired females, or dummy females. However, across the population of recordings, there was a significant relationship between the relative variability of syllable frequency and neural activity: when syllable frequency was less variable to paired than nonpaired females, neural activity was also less variable (and vice-versa). These results show that the lower variability of neural activity and syllable frequency during directed singing is not a binary distinction from undirected singing, but can vary in intensity, possibly related to the relative preference of a male for his singing target. PMID:24312344
The effect of the neural activity on topological properties of growing neural networks.

PubMed

Gafarov, F M; Gafarova, V R

2016-09-01

The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal patterns of network's development, and the process of creation and deletion of connections is continuous in the whole life of the organism. In this paper, we study how neural activity influences the growth process in neural networks. By using a two-dimensional activity-dependent growth model we demonstrated the neural network growth process from disconnected neurons to fully connected networks. For making quantitative investigation of the network's activity influence on its topological properties we compared it with the random growth network not depending on network's activity. By using the random graphs theory methods for the analysis of the network's connections structure it is shown that the growth in neural networks results in the formation of a well-known "small-world" network.
The Amsterdam Resting-State Questionnaire reveals multiple phenotypes of resting-state cognition

PubMed Central

Diaz, B. Alexander; Van Der Sluis, Sophie; Moens, Sarah; Benjamins, Jeroen S.; Migliorati, Filippo; Stoffers, Diederick; Den Braber, Anouk; Poil, Simon-Shlomo; Hardstone, Richard; Van't Ent, Dennis; Boomsma, Dorret I.; De Geus, Eco; Mansvelder, Huibert D.; Van Someren, Eus J. W.; Linkenkaer-Hansen, Klaus

2013-01-01

Resting-state neuroimaging is a dominant paradigm for studying brain function in health and disease. It is attractive for clinical research because of its simplicity for patients, straightforward standardization, and sensitivity to brain disorders. Importantly, non-sensory experiences like mind wandering may arise from ongoing brain activity. However, little is known about the link between ongoing brain activity and cognition, as phenotypes of resting-state cognition—and tools to quantify them—have been lacking. To facilitate rapid and structured measurements of resting-state cognition we developed a 50-item self-report survey, the Amsterdam Resting-State Questionnaire (ARSQ). Based on ARSQ data from 813 participants assessed after 5 min eyes-closed rest in their home, we identified seven dimensions of resting-state cognition using factor analysis: Discontinuity of Mind, Theory of Mind, Self, Planning, Sleepiness, Comfort, and Somatic Awareness. Further, we showed that the structure of cognition was similar during resting-state fMRI and EEG, and that the test-retest correlations were remarkably high for all dimensions. To explore whether inter-individual variation of resting-state cognition is related to health status, we correlated ARSQ-derived factor scores with psychometric scales measuring depression, anxiety, and sleep quality. Mental health correlated positively with Comfort and negatively with Discontinuity of Mind. Finally, we show that sleepiness may partially explain a resting-state EEG profile previously associated with Alzheimer's disease. These findings indicate that the ARSQ readily provides information about cognitive phenotypes and that it is a promising tool for research on the neural correlates of resting-state cognition in health and disease. PMID:23964225

A bilateral cortical network responds to pitch perturbations in speech feedback

PubMed Central

Kort, Naomi S.; Nagarajan, Srikantan S.; Houde, John F.

2014-01-01

Auditory feedback is used to monitor and correct for errors in speech production, and one of the clearest demonstrations of this is the pitch perturbation reflex. During ongoing phonation, speakers respond rapidly to shifts of the pitch of their auditory feedback, altering their pitch production to oppose the direction of the applied pitch shift. In this study, we examine the timing of activity within a network of brain regions thought to be involved in mediating this behavior. To isolate auditory feedback processing relevant for motor control of speech, we used magnetoencephalography (MEG) to compare neural responses to speech onset and to transient (400ms) pitch feedback perturbations during speaking with responses to identical acoustic stimuli during passive listening. We found overlapping, but distinct bilateral cortical networks involved in monitoring speech onset and feedback alterations in ongoing speech. Responses to speech onset during speaking were suppressed in bilateral auditory and left ventral supramarginal gyrus/posterior superior temporal sulcus (vSMG/pSTS). In contrast, during pitch perturbations, activity was enhanced in bilateral vSMG/pSTS, bilateral premotor cortex, right primary auditory cortex, and left higher order auditory cortex. We also found speaking-induced delays in responses to both unaltered and altered speech in bilateral primary and secondary auditory regions, the left vSMG/pSTS and right premotor cortex. The network dynamics reveal the cortical processing involved in both detecting the speech error and updating the motor plan to create the new pitch output. These results implicate vSMG/pSTS as critical in both monitoring auditory feedback and initiating rapid compensation to feedback errors. PMID:24076223
Vertically aligned carbon nanofiber as nano-neuron interface for monitoring neural function.

PubMed

Yu, Zhe; McKnight, Timothy E; Ericson, M Nance; Melechko, Anatoli V; Simpson, Michael L; Morrison, Barclay

2012-05-01

Neural chips, which are capable of simultaneous multisite neural recording and stimulation, have been used to detect and modulate neural activity for almost thirty years. As neural interfaces, neural chips provide dynamic functional information for neural decoding and neural control. By improving sensitivity and spatial resolution, nano-scale electrodes may revolutionize neural detection and modulation at cellular and molecular levels as nano-neuron interfaces. We developed a carbon-nanofiber neural chip with lithographically defined arrays of vertically aligned carbon nanofiber electrodes and demonstrated its capability of both stimulating and monitoring electrophysiological signals from brain tissues in vitro and monitoring dynamic information of neuroplasticity. This novel nano-neuron interface may potentially serve as a precise, informative, biocompatible, and dual-mode neural interface for monitoring of both neuroelectrical and neurochemical activity at the single-cell level and even inside the cell. The authors demonstrate the utility of a neural chip with lithographically defined arrays of vertically aligned carbon nanofiber electrodes. The new device can be used to stimulate and/or monitor signals from brain tissue in vitro and for monitoring dynamic information of neuroplasticity both intracellularly and at the single cell level including neuroelectrical and neurochemical activities. Copyright © 2012 Elsevier Inc. All rights reserved.
Neuronal activity in the globus pallidus internus in patients with tics.

PubMed

Zhuang, P; Hallett, M; Zhang, X; Li, J; Zhang, Y; Li, Y

2009-10-01

To explore the role of neuronal activity in the globus pallidus internus (GPi) in the generation of tic movements. 8 patients with Tourette's syndrome with medically intractable tics who underwent a unilateral pallidotomy for severe tics were studied. They ranged in age from 17 to 24 years; disease duration was 7-19 years. Microelectrode recording was performed in the GPi. The electromyogram (EMG) was simultaneously recorded in muscle groups appropriate for the patient's tics. The relationship between neuronal firing pattern and the EMG was studied. 232 neurons were recorded during tics from eight trajectories. Of these neurons, in addition to decreased neuronal firing rate and irregular firing pattern, 105 (45%) were tic related showing either a burst of activity or a pause in ongoing tonic activity. They could be synchronous (n = 75), earlier than EMG onset (n = 27) or following EMG onset (n = 3). The GPi neuronal bursts preceded EMG onset with decreased (n = 6) or increased activity (n = 21). The initial change in neural activity occurred about 50 ms to 2 s before the EMG onset. Although the data are descriptive and preliminary, the tic related neuronal activity observed in GPi appears to indicate that the basal ganglia motor circuit is involved in tic movements. The early neuronal activity seen in GPi may reflect premonitory sensations that precede a tic.
Neural Activity Patterns in the Human Brain Reflect Tactile Stickiness Perception.

PubMed

Kim, Junsuk; Yeon, Jiwon; Ryu, Jaekyun; Park, Jang-Yeon; Chung, Soon-Cheol; Kim, Sung-Phil

2017-01-01

Our previous human fMRI study found brain activations correlated with tactile stickiness perception using the uni-variate general linear model (GLM) (Yeon et al., 2017). Here, we conducted an in-depth investigation on neural correlates of sticky sensations by employing a multivoxel pattern analysis (MVPA) on the same dataset. In particular, we statistically compared multi-variate neural activities in response to the three groups of sticky stimuli: A supra-threshold group including a set of sticky stimuli that evoked vivid sticky perception; an infra-threshold group including another set of sticky stimuli that barely evoked sticky perception; and a sham group including acrylic stimuli with no physically sticky property. Searchlight MVPAs were performed to search for local activity patterns carrying neural information of stickiness perception. Similar to the uni-variate GLM results, significant multi-variate neural activity patterns were identified in postcentral gyrus, subcortical (basal ganglia and thalamus), and insula areas (insula and adjacent areas). Moreover, MVPAs revealed that activity patterns in posterior parietal cortex discriminated the perceptual intensities of stickiness, which was not present in the uni-variate analysis. Next, we applied a principal component analysis (PCA) to the voxel response patterns within identified clusters so as to find low-dimensional neural representations of stickiness intensities. Follow-up clustering analyses clearly showed separate neural grouping configurations between the Supra- and Infra-threshold groups. Interestingly, this neural categorization was in line with the perceptual grouping pattern obtained from the psychophysical data. Our findings thus suggest that different stickiness intensities would elicit distinct neural activity patterns in the human brain and may provide a neural basis for the perception and categorization of tactile stickiness.
Neural Activity Patterns in the Human Brain Reflect Tactile Stickiness Perception

PubMed Central

Kim, Junsuk; Yeon, Jiwon; Ryu, Jaekyun; Park, Jang-Yeon; Chung, Soon-Cheol; Kim, Sung-Phil

2017-01-01

Our previous human fMRI study found brain activations correlated with tactile stickiness perception using the uni-variate general linear model (GLM) (Yeon et al., 2017). Here, we conducted an in-depth investigation on neural correlates of sticky sensations by employing a multivoxel pattern analysis (MVPA) on the same dataset. In particular, we statistically compared multi-variate neural activities in response to the three groups of sticky stimuli: A supra-threshold group including a set of sticky stimuli that evoked vivid sticky perception; an infra-threshold group including another set of sticky stimuli that barely evoked sticky perception; and a sham group including acrylic stimuli with no physically sticky property. Searchlight MVPAs were performed to search for local activity patterns carrying neural information of stickiness perception. Similar to the uni-variate GLM results, significant multi-variate neural activity patterns were identified in postcentral gyrus, subcortical (basal ganglia and thalamus), and insula areas (insula and adjacent areas). Moreover, MVPAs revealed that activity patterns in posterior parietal cortex discriminated the perceptual intensities of stickiness, which was not present in the uni-variate analysis. Next, we applied a principal component analysis (PCA) to the voxel response patterns within identified clusters so as to find low-dimensional neural representations of stickiness intensities. Follow-up clustering analyses clearly showed separate neural grouping configurations between the Supra- and Infra-threshold groups. Interestingly, this neural categorization was in line with the perceptual grouping pattern obtained from the psychophysical data. Our findings thus suggest that different stickiness intensities would elicit distinct neural activity patterns in the human brain and may provide a neural basis for the perception and categorization of tactile stickiness. PMID:28936171
Altered Neural Activity Associated with Mindfulness during Nociception: A Systematic Review of Functional MRI.

PubMed

Bilevicius, Elena; Kolesar, Tiffany A; Kornelsen, Jennifer

2016-04-19

To assess the neural activity associated with mindfulness-based alterations of pain perception. The Cochrane Central, EMBASE, Ovid Medline, PsycINFO, Scopus, and Web of Science databases were searched on 2 February 2016. Titles, abstracts, and full-text articles were independently screened by two reviewers. Data were independently extracted from records that included topics of functional neuroimaging, pain, and mindfulness interventions. The literature search produced 946 total records, of which five met the inclusion criteria. Records reported pain in terms of anticipation (n = 2), unpleasantness (n = 5), and intensity (n = 5), and how mindfulness conditions altered the neural activity during noxious stimulation accordingly. Although the studies were inconsistent in relating pain components to neural activity, in general, mindfulness was able to reduce pain anticipation and unpleasantness ratings, as well as alter the corresponding neural activity. The major neural underpinnings of mindfulness-based pain reduction consisted of altered activity in the anterior cingulate cortex, insula, and dorsolateral prefrontal cortex.
Neural basis of singing in crickets: central pattern generation in abdominal ganglia

NASA Astrophysics Data System (ADS)

Schöneich, Stefan; Hedwig, Berthold

2011-12-01

The neural mechanisms underlying cricket singing behavior have been the focus of several studies, but the central pattern generator (CPG) for singing has not been localized conclusively. To test if the abdominal ganglia contribute to the singing motor pattern and to analyze if parts of the singing CPG are located in these ganglia, we systematically truncated the abdominal nerve cord of fictively singing crickets while recording the singing motor pattern from a front-wing nerve. Severing the connectives anywhere between terminal ganglion and abdominal ganglion A3 did not preclude singing, although the motor pattern became more variable and failure-prone as more ganglia were disconnected. Singing terminated immediately and permanently after transecting the connectives between the metathoracic ganglion complex and the first unfused abdominal ganglion A3. The contribution of abdominal ganglia for singing pattern generation was confirmed by intracellular interneuron recordings and current injections. During fictive singing, an ascending interneuron with its soma and dendrite in A3 depolarized rhythmically. It spiked 10 ms before the wing-opener activity and hyperpolarized in phase with the wing-closer activity. Depolarizing current injection elicited rhythmic membrane potential oscillations and spike bursts that elicited additional syllables and reliably reset the ongoing chirp rhythm. Our results disclose that the abdominal ganglion A3 is directly involved in generating the singing motor pattern, whereas the more posterior ganglia seem to provide only stabilizing feedback to the CPG circuit. Localizing the singing CPG in the anterior abdominal neuromeres now allows analyzing its circuitry at the level of identified interneurons in subsequent studies.
The response of L5 pyramidal neurons of the PFC to magnetic stimulation from a micro-coil.

PubMed

Lee, Seung Woo; Fried, Shelley I

2014-01-01

Magnetic stimulation of the nervous system, e.g. transcranial magnetic stimulation (TMS), has been used both to unravel basic structure and function of the nervous system as well as to treat neurological diseases, i.e. clinical depression. Despite progress in both areas, ongoing advancements have been limited by a lack of understanding of the mechanism by which magnetic stimulation alters neural activity. Here, we report responses of cortical neurons to magnetic stimulation arising from a sub-millimeter coil. Cell attached patch clamp was used to record neural activity of layer 5/6 pyramidal neurons of the prefrontal cortex (PFC) in the in vitro mouse brain slice preparation. The fields arising from the small coil were quite different from those arising during clinical TMS but nevertheless allowed the responses of cortical neurons to magnetic stimulation to be probed. For example, the focal nature of induced fields allowed the sensitivity of different regions within targeted pyramidal neurons, e.g. apical dendrite, soma and axon hillock, to be compared. We found that PFC pyramidal neurons were not sensitive to single pulses of stimulation regardless of coil location. However, regions of the apical dendrite and proximal axon were both sensitive to repetitive stimulation as long as the orientation of the induced electric field was aligned with the long axis of the neuron. These results suggest that neurons of the PFC are sensitive to weak magnetic fields and further, that this type of approach may be useful for unraveling some of the mechanisms underlying TMS.
Low-level alcohol consumption during adolescence and its impact on cognitive control development.

PubMed

Jurk, Sarah; Mennigen, Eva; Goschke, Thomas; Smolka, Michael N

2018-01-01

Adolescence is a critical period for maturation of cognitive control and most adolescents start experimenting with alcohol around that time. On the one hand, recent studies indicate that low control abilities predict future problematic alcohol use. On the other hand, binge drinking during young adulthood can (further) impair cognitive control. However, so far no study examined the effects of low-level alcohol use during adolescence. In the present longitudinal fMRI study, we therefore investigated the development of cognitive control in a community-based sample of 92 adolescents at ages 14, 16 and 18. Two different cognitive control functions, i.e. inhibition of pre-potent responses (operationalized by incongruence effects) and switching between different task sets, were measured within one task. Alcohol use in our sample was low (mean: 54 g/week at age 18). The study revealed that neither behavioural nor neural measures of cognitive control function at age 14 predicted alcohol use at age 18 but confirmed established predictors such as gender and personality. As expected, from age 14 to 18, cognitive control abilities were improving (decreased reaction times and/or errors), and activation of cognitive control networks (dorsal anterior cingulate cortex and pre-supplementary motor area) during incongruent trials increased. Unexpectedly, higher alcohol consumption during adolescence was associated with a more pronounced increase in cognitive performance and a smaller increase of neural activation when incongruent trials afforded inhibitory control. We conclude that low-level alcohol use during adolescence does not severely impair ongoing maturation of cognitive control abilities and networks. © 2016 Society for the Study of Addiction.
Adolescent neural response to reward is related to participant sex and task motivation.

PubMed

Alarcón, Gabriela; Cservenka, Anita; Nagel, Bonnie J

2017-02-01

Risky decision making is prominent during adolescence, perhaps contributed to by heightened sensation seeking and ongoing maturation of reward and dopamine systems in the brain, which are, in part, modulated by sex hormones. In this study, we examined sex differences in the neural substrates of reward sensitivity during a risky decision-making task and hypothesized that compared with girls, boys would show heightened brain activation in reward-relevant regions, particularly the nucleus accumbens, during reward receipt. Further, we hypothesized that testosterone and estradiol levels would mediate this sex difference. Moreover, we predicted boys would make more risky choices on the task. While boys showed increased nucleus accumbens blood oxygen level-dependent (BOLD) response relative to girls, sex hormones did not mediate this effect. As predicted, boys made a higher percentage of risky decisions during the task. Interestingly, boys also self-reported more motivation to perform well and earn money on the task, while girls self-reported higher state anxiety prior to the scan session. Motivation to earn money partially mediated the effect of sex on nucleus accumbens activity during reward. Previous research shows that increased motivation and salience of reinforcers is linked with more robust striatal BOLD response, therefore psychosocial factors, in addition to sex, may play an important role in reward sensitivity. Elucidating neurobiological mechanisms that support adolescent sex differences in risky decision making has important implications for understanding individual differences that lead to advantageous and adverse behaviors that affect health outcomes. Copyright © 2016 Elsevier Inc. All rights reserved.
The association between brain activity and motor imagery during motor illusion induction by vibratory stimulation

PubMed Central

Kodama, Takayuki; Nakano, Hideki; Katayama, Osamu; Murata, Shin

2017-01-01

Background: The association between motor imagery ability and brain neural activity that leads to the manifestation of a motor illusion remains unclear. Objective: In this study, we examined the association between the ability to generate motor imagery and brain neural activity leading to the induction of a motor illusion by vibratory stimulation. Methods: The sample consisted of 20 healthy individuals who did not have movement or sensory disorders. We measured the time between the starting and ending points of a motor illusion (the time to illusion induction, TII) and performed electroencephalography (EEG). We conducted a temporo-spatial analysis on brain activity leading to the induction of motor illusions using the EEG microstate segmentation method. Additionally, we assessed the ability to generate motor imagery using the Japanese version of the Movement Imagery Questionnaire-Revised (JMIQ-R) prior to performing the task and examined the associations among brain neural activity levels as identified by microstate segmentation method, TII, and the JMIQ-R scores. Results: The results showed four typical microstates during TII and significantly higher neural activity in the ventrolateral prefrontal cortex, primary sensorimotor area, supplementary motor area (SMA), and inferior parietal lobule (IPL). Moreover, there were significant negative correlations between the neural activity of the primary motor cortex (MI), SMA, IPL, and TII, and a significant positive correlation between the neural activity of the SMA and the JMIQ-R scores. Conclusion: These findings suggest the possibility that a neural network primarily comprised of the neural activity of SMA and M1, which are involved in generating motor imagery, may be the neural basis for inducing motor illusions. This may aid in creating a new approach to neurorehabilitation that enables a more robust reorganization of the neural base for patients with brain dysfunction with a motor function disorder. PMID:29172013
Orphan nuclear receptor TLX activates Wnt/β-catenin signalling to stimulate neural stem cell proliferation and self-renewal

PubMed Central

Qu, Qiuhao; Sun, Guoqiang; Li, Wenwu; Yang, Su; Ye, Peng; Zhao, Chunnian; Yu, Ruth T.; Gage, Fred H.; Evans, Ronald M.; Shi, Yanhong

2010-01-01

The nuclear receptor TLX (also known as NR2E1) is essential for adult neural stem cell self-renewal; however, the molecular mechanisms involved remain elusive. Here we show that TLX activates the canonical Wnt/β-catenin pathway in adult mouse neural stem cells. Furthermore, we demonstrate that Wnt/β-catenin signalling is important in the proliferation and self-renewal of adult neural stem cells in the presence of epidermal growth factor and fibroblast growth factor. Wnt7a and active β-catenin promote neural stem cell self-renewal, whereas the deletion of Wnt7a or the lentiviral transduction of axin, a β-catenin inhibitor, led to decreased cell proliferation in adult neurogenic areas. Lentiviral transduction of active β-catenin led to increased numbers of type B neural stem cells in the subventricular zone of adult brains, whereas deletion of Wnt7a or TLX resulted in decreased numbers of neural stem cells retaining bromodeoxyuridine label in the adult brain. Both Wnt7a and active β-catenin significantly rescued a TLX (also known as Nr2e1) short interfering RNA-induced deficiency in neural stem cell proliferation. Lentiviral transduction of an active β-catenin increased cell proliferation in neurogenic areas of TLX-null adult brains markedly. These results strongly support the hypothesis that TLX acts through the Wnt/β-catenin pathway to regulate neural stem cell proliferation and self-renewal. Moreover, this study suggests that neural stem cells can promote their own self-renewal by secreting signalling molecules that act in an autocrine/paracrine mode. PMID:20010817
Orphan nuclear receptor TLX activates Wnt/beta-catenin signalling to stimulate neural stem cell proliferation and self-renewal.

PubMed

Qu, Qiuhao; Sun, Guoqiang; Li, Wenwu; Yang, Su; Ye, Peng; Zhao, Chunnian; Yu, Ruth T; Gage, Fred H; Evans, Ronald M; Shi, Yanhong

2010-01-01

The nuclear receptor TLX (also known as NR2E1) is essential for adult neural stem cell self-renewal; however, the molecular mechanisms involved remain elusive. Here we show that TLX activates the canonical Wnt/beta-catenin pathway in adult mouse neural stem cells. Furthermore, we demonstrate that Wnt/beta-catenin signalling is important in the proliferation and self-renewal of adult neural stem cells in the presence of epidermal growth factor and fibroblast growth factor. Wnt7a and active beta-catenin promote neural stem cell self-renewal, whereas the deletion of Wnt7a or the lentiviral transduction of axin, a beta-catenin inhibitor, led to decreased cell proliferation in adult neurogenic areas. Lentiviral transduction of active beta-catenin led to increased numbers of type B neural stem cells in the subventricular zone of adult brains, whereas deletion of Wnt7a or TLX resulted in decreased numbers of neural stem cells retaining bromodeoxyuridine label in the adult brain. Both Wnt7a and active beta-catenin significantly rescued a TLX (also known as Nr2e1) short interfering RNA-induced deficiency in neural stem cell proliferation. Lentiviral transduction of an active beta-catenin increased cell proliferation in neurogenic areas of TLX-null adult brains markedly. These results strongly support the hypothesis that TLX acts through the Wnt/beta-catenin pathway to regulate neural stem cell proliferation and self-renewal. Moreover, this study suggests that neural stem cells can promote their own self-renewal by secreting signalling molecules that act in an autocrine/paracrine mode.
Resting-state brain activity in the motor cortex reflects task-induced activity: A multi-voxel pattern analysis.

PubMed

Kusano, Toshiki; Kurashige, Hiroki; Nambu, Isao; Moriguchi, Yoshiya; Hanakawa, Takashi; Wada, Yasuhiro; Osu, Rieko

2015-08-01

It has been suggested that resting-state brain activity reflects task-induced brain activity patterns. In this study, we examined whether neural representations of specific movements can be observed in the resting-state brain activity patterns of motor areas. First, we defined two regions of interest (ROIs) to examine brain activity associated with two different behavioral tasks. Using multi-voxel pattern analysis with regularized logistic regression, we designed a decoder to detect voxel-level neural representations corresponding to the tasks in each ROI. Next, we applied the decoder to resting-state brain activity. We found that the decoder discriminated resting-state neural activity with accuracy comparable to that associated with task-induced neural activity. The distribution of learned weighted parameters for each ROI was similar for resting-state and task-induced activities. Large weighted parameters were mainly located on conjunctive areas. Moreover, the accuracy of detection was higher than that for a decoder whose weights were randomly shuffled, indicating that the resting-state brain activity includes multi-voxel patterns similar to the neural representation for the tasks. Therefore, these results suggest that the neural representation of resting-state brain activity is more finely organized and more complex than conventionally considered.
Noradrenergic modulation of neural erotic stimulus perception.

PubMed

Graf, Heiko; Wiegers, Maike; Metzger, Coraline Danielle; Walter, Martin; Grön, Georg; Abler, Birgit

2017-09-01

We recently investigated neuromodulatory effects of the noradrenergic agent reboxetine and the dopamine receptor affine amisulpride in healthy subjects on dynamic erotic stimulus processing. Whereas amisulpride left sexual functions and neural activations unimpaired, we observed detrimental activations under reboxetine within the caudate nucleus corresponding to motivational components of sexual behavior. However, broadly impaired subjective sexual functioning under reboxetine suggested effects on further neural components. We now investigated the same sample under these two agents with static erotic picture stimulation as alternative stimulus presentation mode to potentially observe further neural treatment effects of reboxetine. 19 healthy males were investigated under reboxetine, amisulpride and placebo for 7 days each within a double-blind cross-over design. During fMRI static erotic picture were presented with preceding anticipation periods. Subjective sexual functions were assessed by a self-reported questionnaire. Neural activations were attenuated within the caudate nucleus, putamen, ventral striatum, the pregenual and anterior midcingulate cortex and in the orbitofrontal cortex under reboxetine. Subjective diminished sexual arousal under reboxetine was correlated with attenuated neural reactivity within the posterior insula. Again, amisulpride left neural activations along with subjective sexual functioning unimpaired. Neither reboxetine nor amisulpride altered differential neural activations during anticipation of erotic stimuli. Our results verified detrimental effects of noradrenergic agents on neural motivational but also emotional and autonomic components of sexual behavior. Considering the overlap of neural network alterations with those evoked by serotonergic agents, our results suggest similar neuromodulatory effects of serotonergic and noradrenergic agents on common neural pathways relevant for sexual behavior. Copyright © 2017 Elsevier B.V. and ECNP. All rights reserved.
Self-reported empathy and neural activity during action imitation and observation in schizophrenia

PubMed Central

Horan, William P.; Iacoboni, Marco; Cross, Katy A.; Korb, Alex; Lee, Junghee; Nori, Poorang; Quintana, Javier; Wynn, Jonathan K.; Green, Michael F.

2014-01-01

Introduction Although social cognitive impairments are key determinants of functional outcome in schizophrenia their neural bases are poorly understood. This study investigated neural activity during imitation and observation of finger movements and facial expressions in schizophrenia, and their correlates with self-reported empathy. Methods 23 schizophrenia outpatients and 23 healthy controls were studied with functional magnetic resonance imaging (fMRI) while they imitated, executed, or simply observed finger movements and facial emotional expressions. Between-group activation differences, as well as relationships between activation and self-reported empathy, were evaluated. Results Both patients and controls similarly activated neural systems previously associated with these tasks. We found no significant between-group differences in task-related activations. There were, however, between-group differences in the correlation between self-reported empathy and right inferior frontal (pars opercularis) activity during observation of facial emotional expressions. As in previous studies, controls demonstrated a positive association between brain activity and empathy scores. In contrast, the pattern in the patient group reflected a negative association between brain activity and empathy. Conclusions Although patients with schizophrenia demonstrated largely normal patterns of neural activation across the finger movement and facial expression tasks, they reported decreased self perceived empathy and failed to show the typical relationship between neural activity and self-reported empathy seen in controls. These findings suggest that patients show a disjunction between automatic neural responses to low level social cues and higher level, integrative social cognitive processes involved in self-perceived empathy. PMID:25009771
Self-reported empathy and neural activity during action imitation and observation in schizophrenia.

PubMed

Horan, William P; Iacoboni, Marco; Cross, Katy A; Korb, Alex; Lee, Junghee; Nori, Poorang; Quintana, Javier; Wynn, Jonathan K; Green, Michael F

2014-01-01

Although social cognitive impairments are key determinants of functional outcome in schizophrenia their neural bases are poorly understood. This study investigated neural activity during imitation and observation of finger movements and facial expressions in schizophrenia, and their correlates with self-reported empathy. 23 schizophrenia outpatients and 23 healthy controls were studied with functional magnetic resonance imaging (fMRI) while they imitated, executed, or simply observed finger movements and facial emotional expressions. Between-group activation differences, as well as relationships between activation and self-reported empathy, were evaluated. Both patients and controls similarly activated neural systems previously associated with these tasks. We found no significant between-group differences in task-related activations. There were, however, between-group differences in the correlation between self-reported empathy and right inferior frontal (pars opercularis) activity during observation of facial emotional expressions. As in previous studies, controls demonstrated a positive association between brain activity and empathy scores. In contrast, the pattern in the patient group reflected a negative association between brain activity and empathy. Although patients with schizophrenia demonstrated largely normal patterns of neural activation across the finger movement and facial expression tasks, they reported decreased self perceived empathy and failed to show the typical relationship between neural activity and self-reported empathy seen in controls. These findings suggest that patients show a disjunction between automatic neural responses to low level social cues and higher level, integrative social cognitive processes involved in self-perceived empathy.
Ensemble Response in Mushroom Body Output Neurons of the Honey Bee Outpaces Spatiotemporal Odor Processing Two Synapses Earlier in the Antennal Lobe

PubMed Central

Strube-Bloss, Martin F.; Herrera-Valdez, Marco A.; Smith, Brian H.

2012-01-01

Neural representations of odors are subject to computations that involve sequentially convergent and divergent anatomical connections across different areas of the brains in both mammals and insects. Furthermore, in both mammals and insects higher order brain areas are connected via feedback connections. In order to understand the transformations and interactions that this connectivity make possible, an ideal experiment would compare neural responses across different, sequential processing levels. Here we present results of recordings from a first order olfactory neuropile – the antennal lobe (AL) – and a higher order multimodal integration and learning center – the mushroom body (MB) – in the honey bee brain. We recorded projection neurons (PN) of the AL and extrinsic neurons (EN) of the MB, which provide the outputs from the two neuropils. Recordings at each level were made in different animals in some experiments and simultaneously in the same animal in others. We presented two odors and their mixture to compare odor response dynamics as well as classification speed and accuracy at each neural processing level. Surprisingly, the EN ensemble significantly starts separating odor stimuli rapidly and before the PN ensemble has reached significant separation. Furthermore the EN ensemble at the MB output reaches a maximum separation of odors between 84–120 ms after odor onset, which is 26 to 133 ms faster than the maximum separation at the AL output ensemble two synapses earlier in processing. It is likely that a subset of very fast PNs, which respond before the ENs, may initiate the rapid EN ensemble response. We suggest therefore that the timing of the EN ensemble activity would allow retroactive integration of its signal into the ongoing computation of the AL via centrifugal feedback. PMID:23209711
Habenula and interpeduncular nucleus differentially modulate predator odor-induced innate fear behavior in rats.

PubMed

Vincenz, Daniel; Wernecke, Kerstin E A; Fendt, Markus; Goldschmidt, Jürgen

2017-08-14

Fear is an important behavioral system helping humans and animals to survive potentially dangerous situations. Fear can be innate or learned. Whereas the neural circuits underlying learned fear are already well investigated, the knowledge about the circuits mediating innate fear is still limited. We here used a novel, unbiased approach to image in vivo the spatial patterns of neural activity in odor-induced innate fear behavior in rats. We intravenously injected awake unrestrained rats with a 99m-technetium labeled blood flow tracer (99mTc-HMPAO) during ongoing exposure to fox urine or water as control, and mapped the brain distribution of the trapped tracer using single-photon emission computed tomography (SPECT). Upon fox urine exposure blood flow increased in a number of brain regions previously associated with odor-induced innate fear such as the amygdala, ventromedial hypothalamus and dorsolateral periaqueductal grey, but, unexpectedly, decreased at higher significance levels in the interpeduncular nucleus (IPN). Significant flow changes were found in regions monosynaptically connected to the IPN. Flow decreased in the dorsal tegmentum and entorhinal cortex. Flow increased in the habenula (Hb) and correlated with odor effects on behavioral defensive strategy. Hb lesions reduced avoidance of but increased approach to the fox urine while IPN lesions only reduced avoidance behavior without approach behavior. Our study identifies a new component, the IPN, of the neural circuit mediating odor-induced innate fear behavior in mammals and suggests that the evolutionarily conserved Hb-IPN system, which has recently been implicated in cued fear, also forms an integral part of the innate fear circuitry. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
Neural Activity in the Ventral Pallidum Encodes Variation in the Incentive Value of a Reward Cue

PubMed Central

Meyer, Paul J.; Ferguson, Lindsay M.; Robinson, Terry E.; Aldridge, J. Wayne

2016-01-01

There is considerable individual variation in the extent to which reward cues are attributed with incentive salience. For example, a food-predictive conditioned stimulus (CS; an illuminated lever) becomes attractive, eliciting approach toward it only in some rats (“sign trackers,” STs), whereas others (“goal trackers,” GTs) approach the food cup during the CS period. The purpose of this study was to determine how individual differences in Pavlovian approach responses are represented in neural firing patterns in the major output structure of the mesolimbic system, the ventral pallidum (VP). Single-unit in vivo electrophysiology was used to record neural activity in the caudal VP during the performance of ST and GT conditioned responses. All rats showed neural responses to both cue onset and reward delivery but, during the CS period, STs showed greater neural activity than GTs both in terms of the percentage of responsive neurons and the magnitude of the change in neural activity. Furthermore, neural activity was positively correlated with the degree of attraction to the cue. Given that the CS had equal predictive value in STs and GTs, we conclude that neural activity in the VP largely reflects the degree to which the CS was attributed with incentive salience. SIGNIFICANCE STATEMENT Cues associated with reward can acquire motivational properties (i.e., incentive salience) that cause them to have a powerful influence on desire and motivated behavior. There are individual differences in sensitivity to reward-paired cues, with some individuals attaching greater motivational value to cues than others. Here, we investigated the neural activity associated with these individual differences in incentive salience. We found that cue-evoked neural firing in the ventral pallidum (VP) reflected the strength of incentive motivation, with the greatest neural responses occurring in individuals that demonstrated the strongest attraction to the cue. This suggests that the VP plays an important role in the process by which cues gain control over motivation and behavior. PMID:27466340

Cannabis and alcohol use, and the developing brain.

PubMed

Meruelo, A D; Castro, N; Cota, C I; Tapert, S F

2017-05-15

Sex hormones and white (and grey) matter in the limbic system, cortex and other brain regions undergo changes during adolescence. Some of these changes include ongoing white matter myelination and sexually dimorphic features in grey and white matter. Adolescence is also a period of vulnerability when many are first exposed to alcohol and cannabis, which appear to influence the developing brain. Neuropsychological studies have provided considerable understanding of the effects of alcohol and cannabis on the brain. Advances in neuroimaging have allowed examination of neuroanatomic changes, metabolic and neurotransmitter activity, and neuronal activation during adolescent brain development and substance use. In this review, we examine major differences in brain development between users and non-users, and recent findings on the influence of cannabis and alcohol on the adolescent brain. We also discuss associations that appear to resolve following short-term abstinence, and attentional deficits that appear to persist. These findings can be useful in guiding earlier educational interventions for adolescents, and clarifying the neural sequelae of early alcohol and cannabis use to the general public. Copyright © 2017 Elsevier B.V. All rights reserved.
Synchronized delta oscillations correlate with the resting-state functional MRI signal

PubMed Central

Lu, Hanbing; Zuo, Yantao; Gu, Hong; Waltz, James A.; Zhan, Wang; Scholl, Clara A.; Rea, William; Yang, Yihong; Stein, Elliot A.

2007-01-01

Synchronized low-frequency spontaneous fluctuations of the functional MRI (fMRI) signal have recently been applied to investigate large-scale neuronal networks of the brain in the absence of specific task instructions. However, the underlying neural mechanisms of these fluctuations remain largely unknown. To this end, electrophysiological recordings and resting-state fMRI measurements were conducted in α-chloralose-anesthetized rats. Using a seed-voxel analysis strategy, region-specific, anesthetic dose-dependent fMRI resting-state functional connectivity was detected in bilateral primary somatosensory cortex (S1FL) of the resting brain. Cortical electroencephalographic signals were also recorded from bilateral S1FL; a visual cortex locus served as a control site. Results demonstrate that, unlike the evoked fMRI response that correlates with power changes in the γ bands, the resting-state fMRI signal correlates with the power coherence in low-frequency bands, particularly the δ band. These data indicate that hemodynamic fMRI signal differentially registers specific electrical oscillatory frequency band activity, suggesting that fMRI may be able to distinguish the ongoing from the evoked activity of the brain. PMID:17991778
Cannabis and Alcohol Use, and the Developing Brain

PubMed Central

Meruelo, AD; Castro, N; Cota, CI; Tapert, SF

2017-01-01

Sex hormones and white (and grey) matter in the limbic system, cortex and other brain regions undergo changes during adolescence. Some of these changes include ongoing white matter myelination and sexually dimorphic features in grey and white matter. Adolescence is also a period of vulnerability when many are first exposed to alcohol and cannabis, which appear to influence the developing brain. Neuropsychological studies have provided considerable understanding of the effects of alcohol and cannabis on the brain. Advances in neuroimaging have allowed examination of neuroanatomic changes, metabolic and neurotransmitter activity, and neuronal activation during adolescent brain development and substance use. In this review, we examine major differences in brain development between users and non-users, and recent findings on the influence of cannabis and alcohol on the adolescent brain. We also discuss associations that appear to resolve following short-term abstinence, and attentional deficits that appear to persist. These findings can be useful in guiding earlier educational interventions for adolescents, and clarifying the neural sequelae of early alcohol and cannabis use to the general public. PMID:28223098
A scalable population code for time in the striatum.

PubMed

Mello, Gustavo B M; Soares, Sofia; Paton, Joseph J

2015-05-04

To guide behavior and learn from its consequences, the brain must represent time over many scales. Yet, the neural signals used to encode time in the seconds-to-minute range are not known. The striatum is a major input area of the basal ganglia associated with learning and motor function. Previous studies have also shown that the striatum is necessary for normal timing behavior. To address how striatal signals might be involved in timing, we recorded from striatal neurons in rats performing an interval timing task. We found that neurons fired at delays spanning tens of seconds and that this pattern of responding reflected the interaction between time and the animals' ongoing sensorimotor state. Surprisingly, cells rescaled responses in time when intervals changed, indicating that striatal populations encoded relative time. Moreover, time estimates decoded from activity predicted timing behavior as animals adjusted to new intervals, and disrupting striatal function led to a decrease in timing performance. These results suggest that striatal activity forms a scalable population code for time, providing timing signals that animals use to guide their actions. Copyright © 2015 Elsevier Ltd. All rights reserved.
Stuttering, induced fluency, and natural fluency: a hierarchical series of activation likelihood estimation meta-analyses.

PubMed

Budde, Kristin S; Barron, Daniel S; Fox, Peter T

2014-12-01

Developmental stuttering is a speech disorder most likely due to a heritable form of developmental dysmyelination impairing the function of the speech-motor system. Speech-induced brain-activation patterns in persons who stutter (PWS) are anomalous in various ways; the consistency of these aberrant patterns is a matter of ongoing debate. Here, we present a hierarchical series of coordinate-based meta-analyses addressing this issue. Two tiers of meta-analyses were performed on a 17-paper dataset (202 PWS; 167 fluent controls). Four large-scale (top-tier) meta-analyses were performed, two for each subject group (PWS and controls). These analyses robustly confirmed the regional effects previously postulated as "neural signatures of stuttering" (Brown, Ingham, Ingham, Laird, & Fox, 2005) and extended this designation to additional regions. Two smaller-scale (lower-tier) meta-analyses refined the interpretation of the large-scale analyses: (1) a between-group contrast targeting differences between PWS and controls (stuttering trait); and (2) a within-group contrast (PWS only) of stuttering with induced fluency (stuttering state). Copyright © 2014 Elsevier Inc. All rights reserved.
Assessing Change in Agricultural Productivity Caused by Drought and Conflict in Northern Syria using Landsat Imagery.

NASA Astrophysics Data System (ADS)

Girgin, T.; Ozdogan, M.

2015-12-01

Until recently, agricultural production in Syria has been an important source of revenue and food security for the country. At its peak, agriculture in Syria accounted for 25 percent of the country's GDP. In 2014, Syrian agriculture accounted for less than 5 percent of the GDP. This decline in agricultural productivity is the cause of a 3-year long drought that started in 2007, followed by a still-ongoing conflict that started in mid-2011. Using remote sensing tools, this paper focuses on the impact that the 2007-2010 drought had on agricultural production, as well as the impact that the ongoing conflict had on the agricultural production in northern Syria. Remote sensing is a powerful and great solution to study regions of the world that are hard-to-reach due to conflict and/or other limitations. It is particularly useful when studying a region that inaccessible due to an ongoing conflict, such as in northern Syria. Using multi-temporal Landsat 5 and Landsat 8 images from August 2006, 2010 and 2014 and utilizing the neural networks algorithm, we assessed for agricultural output change in northern Syria. We conclude that the ongoing Syrian conflict has had a bigger impact on the agricultural output in northern Syria than the 3-year long drought.
Vertically aligned carbon nanofiber as nano-neuron interface for monitoring neural function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ericson, Milton Nance; McKnight, Timothy E; Melechko, Anatoli Vasilievich

2012-01-01

Neural chips, which are capable of simultaneous, multi-site neural recording and stimulation, have been used to detect and modulate neural activity for almost 30 years. As a neural interface, neural chips provide dynamic functional information for neural decoding and neural control. By improving sensitivity and spatial resolution, nano-scale electrodes may revolutionize neural detection and modulation at cellular and molecular levels as nano-neuron interfaces. We developed a carbon-nanofiber neural chip with lithographically defined arrays of vertically aligned carbon nanofiber electrodes and demonstrated its capability of both stimulating and monitoring electrophysiological signals from brain tissues in vitro and monitoring dynamic information ofmore » neuroplasticity. This novel nano-neuron interface can potentially serve as a precise, informative, biocompatible, and dual-mode neural interface for monitoring of both neuroelectrical and neurochemical activity at the single cell level and even inside the cell.« less
Neural circuits via which single prolonged stress exposure leads to fear extinction retention deficits

PubMed Central

Stanfield, Briana R.; Staib, Jennifer M.; David, Nina P.; Keller, Samantha M.; DePietro, Thomas

2016-01-01

Single prolonged stress (SPS) has been used to examine mechanisms via which stress exposure leads to post-traumatic stress disorder symptoms. SPS induces fear extinction retention deficits, but neural circuits critical for mediating these deficits are unknown. To address this gap, we examined the effect of SPS on neural activity in brain regions critical for extinction retention (i.e., fear extinction circuit). These were the ventral hippocampus (vHipp), dorsal hippocampus (dHipp), basolateral amygdala (BLA), prelimbic cortex (PL), and infralimbic cortex (IL). SPS or control rats were fear conditioned then subjected to extinction training and testing. Subsets of rats were euthanized after extinction training, extinction testing, or immediate removal from the housing colony (baseline condition) to assay c-Fos levels (measure of neural activity) in respective brain region. SPS induced extinction retention deficits. During extinction training SPS disrupted enhanced IL neural activity and inhibited BLA neural activity. SPS also disrupted inhibited BLA and vHipp neural activity during extinction testing. Statistical analyses suggested that SPS disrupted functional connectivity within the dHipp during extinction training and increased functional connectivity between the BLA and vHipp during extinction testing. Our findings suggest that SPS induces extinction retention deficits by disrupting both excitatory and inhibitory changes in neural activity within the fear extinction circuit and inducing changes in functional connectivity within the Hipp and BLA. PMID:27918273
Inactivity-induced phrenic and hypoglossal motor facilitation are differentially expressed following intermittent vs. sustained neural apnea

PubMed Central

Baertsch, N. A.

2013-01-01

Reduced respiratory neural activity elicits a rebound increase in phrenic and hypoglossal motor output known as inactivity-induced phrenic and hypoglossal motor facilitation (iPMF and iHMF, respectively). We hypothesized that, similar to other forms of respiratory plasticity, iPMF and iHMF are pattern sensitive. Central respiratory neural activity was reversibly reduced in ventilated rats by hyperventilating below the CO2 apneic threshold to create brief intermittent neural apneas (5, ∼1.5 min each, separated by 5 min), a single brief massed neural apnea (7.5 min), or a single prolonged neural apnea (30 min). Upon restoration of respiratory neural activity, long-lasting (>60 min) iPMF was apparent following brief intermittent and prolonged, but not brief massed, neural apnea. Further, brief intermittent and prolonged neural apnea elicited an increase in the maximum phrenic response to high CO2, suggesting that iPMF is associated with an increase in phrenic dynamic range. By contrast, only prolonged neural apnea elicited iHMF, which was transient in duration (<15 min). Intermittent, massed, and prolonged neural apnea all elicited a modest transient facilitation of respiratory frequency. These results indicate that iPMF, but not iHMF, is pattern sensitive, and that the response to respiratory neural inactivity is motor pool specific. PMID:23493368
Development of an aversive Pavlovian-to-instrumental transfer task in rat

PubMed Central

Campese, Vincent; McCue, Margaret; Lázaro-Muñoz, Gabriel; LeDoux, Joseph E.; Cain, Christopher K.

2013-01-01

Pavlovian-to-instrumental transfer (PIT) is an effect whereby a classically conditioned stimulus (CS) enhances ongoing instrumental responding. PIT has been extensively studied with appetitive conditioning but barely at all with aversive conditioning. Although it's been argued that conditioned suppression is a form of aversive PIT, this effect is fundamentally different from appetitive PIT because the CS suppresses, instead of facilitates, responding. Five experiments investigated the importance of a variety of factors on aversive PIT in a rodent Sidman avoidance paradigm in which ongoing shuttling behavior (unsignaled active avoidance or USAA) was facilitated by an aversive CS. Experiment 1 demonstrated a basic PIT effect. Experiment 2 found that a moderate amount of USAA extinction produces the strongest PIT with shuttling rates best at around 2 responses per minute prior to the CS. Experiment 3 tested a protocol in which the USAA behavior was required to reach the 2-response per minute mark in order to trigger the CS presentation and found that this produced robust and reliable PIT. Experiment 4 found that the Pavlovian conditioning US intensity was not a major determinant of PIT strength. Experiment 5 demonstrated that if the CS and US were not explicitly paired during Pavlovian conditioning, PIT did not occur, showing that CS-US learning is required. Together, these studies demonstrate a robust, reliable and stable aversive PIT effect that is amenable to analysis of neural circuitry. PMID:24324417
Influence of DAT1 and COMT variants on neural activation during response inhibition in adolescents with attention-deficit/hyperactivity disorder and healthy controls.

PubMed

van Rooij, D; Hoekstra, P J; Bralten, J; Hakobjan, M; Oosterlaan, J; Franke, B; Rommelse, N; Buitelaar, J K; Hartman, C A

2015-11-01

Impairment of response inhibition has been implicated in attention-deficit/hyperactivity disorder (ADHD). Dopamine neurotransmission has been linked to the behavioural and neural correlates of response inhibition. The current study aimed to investigate the relationship of polymorphisms in two dopamine-related genes, the catechol-O-methyltransferase gene (COMT) and the dopamine transporter gene (SLC6A3 or DAT1), with the neural and behavioural correlates of response inhibition. Behavioural and neural measures of response inhibition were obtained in 185 adolescents with ADHD, 111 of their unaffected siblings and 124 healthy controls (mean age 16.9 years). We investigated the association of DAT1 and COMT variants on task performance and whole-brain neural activation during response inhibition in a hypothesis-free manner. Additionally, we attempted to explain variance in previously found ADHD effects on neural activation during response inhibition using these DAT1 and COMT polymorphisms. The whole-brain analyses demonstrated large-scale neural activation changes in the medial and lateral prefrontal, subcortical and parietal regions of the response inhibition network in relation to DAT1 and COMT polymorphisms. Although these neural activation changes were associated with different task performance measures, no relationship was found between DAT1 or COMT variants and ADHD, nor did variants in these genes explain variance in the effects of ADHD on neural activation. These results suggest that dopamine-related genes play a role in the neurobiology of response inhibition. The limited associations between gene polymorphisms and task performance further indicate the added value of neural measures in linking genetic factors and behavioural measures.
A neural mechanism of speed-accuracy tradeoff in macaque area LIP

PubMed Central

Hanks, Timothy; Kiani, Roozbeh; Shadlen, Michael N

2014-01-01

Decision making often involves a tradeoff between speed and accuracy. Previous studies indicate that neural activity in the lateral intraparietal area (LIP) represents the gradual accumulation of evidence toward a threshold level, or evidence bound, which terminates the decision process. The level of this bound is hypothesized to mediate the speed-accuracy tradeoff. To test this, we recorded from LIP while monkeys performed a motion discrimination task in two speed-accuracy regimes. Surprisingly, the terminating threshold levels of neural activity were similar in both regimes. However, neurons recorded in the faster regime exhibited stronger evidence-independent activation from the beginning of decision formation, effectively reducing the evidence-dependent neural modulation needed for choice commitment. Our results suggest that control of speed vs accuracy may be exerted through changes in decision-related neural activity itself rather than through changes in the threshold applied to such neural activity to terminate a decision. DOI: http://dx.doi.org/10.7554/eLife.02260.001 PMID:24867216
Beta band oscillations in motor cortex reflect neural population signals that delay movement onset

PubMed Central

Khanna, Preeya; Carmena, Jose M

2017-01-01

Motor cortical beta oscillations have been reported for decades, yet their behavioral correlates remain unresolved. Some studies link beta oscillations to changes in underlying neural activity, but the specific behavioral manifestations of these reported changes remain elusive. To investigate how changes in population neural activity, beta oscillations, and behavior are linked, we recorded multi-scale neural activity from motor cortex while three macaques performed a novel neurofeedback task. Subjects volitionally brought their beta oscillatory power to an instructed state and subsequently executed an arm reach. Reaches preceded by a reduction in beta power exhibited significantly faster movement onset times than reaches preceded by an increase in beta power. Further, population neural activity was found to shift farther from a movement onset state during beta oscillations that were neurofeedback-induced or naturally occurring during reaching tasks. This finding establishes a population neural basis for slowed movement onset following periods of beta oscillatory activity. DOI: http://dx.doi.org/10.7554/eLife.24573.001 PMID:28467303
Identifying the neural substrates of intrinsic motivation during task performance.

PubMed

Lee, Woogul; Reeve, Johnmarshall

2017-10-01

Intrinsic motivation is the inherent tendency to seek out novelty and challenge, to explore and investigate, and to stretch and extend one's capacities. When people imagine performing intrinsically motivating tasks, they show heightened anterior insular cortex (AIC) activity. To fully explain the neural system of intrinsic motivation, however, requires assessing neural activity while people actually perform intrinsically motivating tasks (i.e., while answering curiosity-inducing questions or solving competence-enabling anagrams). Using event-related functional magnetic resonance imaging, we found that the neural system of intrinsic motivation involves not only AIC activity, but also striatum activity and, further, AIC-striatum functional interactions. These findings suggest that subjective feelings of intrinsic satisfaction (associated with AIC activations), reward processing (associated with striatum activations), and their interactions underlie the actual experience of intrinsic motivation. These neural findings are consistent with the conceptualization of intrinsic motivation as the pursuit and satisfaction of subjective feelings (interest and enjoyment) as intrinsic rewards.
From homeostasis to behavior: Balanced activity in an exploration of embodied dynamic environmental-neural interaction.

PubMed

Hellyer, Peter John; Clopath, Claudia; Kehagia, Angie A; Turkheimer, Federico E; Leech, Robert

2017-08-01

In recent years, there have been many computational simulations of spontaneous neural dynamics. Here, we describe a simple model of spontaneous neural dynamics that controls an agent moving in a simple virtual environment. These dynamics generate interesting brain-environment feedback interactions that rapidly destabilize neural and behavioral dynamics demonstrating the need for homeostatic mechanisms. We investigate roles for homeostatic plasticity both locally (local inhibition adjusting to balance excitatory input) as well as more globally (regional "task negative" activity that compensates for "task positive", sensory input in another region) balancing neural activity and leading to more stable behavior (trajectories through the environment). Our results suggest complementary functional roles for both local and macroscale mechanisms in maintaining neural and behavioral dynamics and a novel functional role for macroscopic "task-negative" patterns of activity (e.g., the default mode network).
Sustained selective attention to competing amplitude-modulations in human auditory cortex.

PubMed

Riecke, Lars; Scharke, Wolfgang; Valente, Giancarlo; Gutschalk, Alexander

2014-01-01

Auditory selective attention plays an essential role for identifying sounds of interest in a scene, but the neural underpinnings are still incompletely understood. Recent findings demonstrate that neural activity that is time-locked to a particular amplitude-modulation (AM) is enhanced in the auditory cortex when the modulated stream of sounds is selectively attended to under sensory competition with other streams. However, the target sounds used in the previous studies differed not only in their AM, but also in other sound features, such as carrier frequency or location. Thus, it remains uncertain whether the observed enhancements reflect AM-selective attention. The present study aims at dissociating the effect of AM frequency on response enhancement in auditory cortex by using an ongoing auditory stimulus that contains two competing targets differing exclusively in their AM frequency. Electroencephalography results showed a sustained response enhancement for auditory attention compared to visual attention, but not for AM-selective attention (attended AM frequency vs. ignored AM frequency). In contrast, the response to the ignored AM frequency was enhanced, although a brief trend toward response enhancement occurred during the initial 15 s. Together with the previous findings, these observations indicate that selective enhancement of attended AMs in auditory cortex is adaptive under sustained AM-selective attention. This finding has implications for our understanding of cortical mechanisms for feature-based attentional gain control.
ERP effects and perceived exclusion in the Cyberball paradigm: Correlates of expectancy violation?

PubMed

Weschke, Sarah; Niedeggen, Michael

2015-10-22

A virtual ball-tossing game called Cyberball has allowed the identification of neural structures involved in the processing of social exclusion by using neurocognitive methods. However, there is still an ongoing debate if structures involved are either pain- or exclusion-specific or part of a broader network. In electrophysiological Cyberball studies we have shown that the P3b component is sensitive to exclusion manipulations, possibly modulated by the probability of ball possession of the participant (event "self") or the presumed co-players (event "other"). Since it is known from oddball studies that the P3b is not only modulated by the objective probability of an event, but also by subjective expectancy, we independently manipulated the probability of the events "self" and "other" and the expectancy for these events. Questionnaire data indicate that social need threat is only induced when the expectancy for involvement in the ball-tossing game is violated. Similarly, the P3b amplitude of both "self" and "other" events was a correlate of expectancy violation. We conclude that both the subjective report of exclusion and the P3b effect induced in the Cyberball paradigm are primarily based on a cognitive process sensitive to expectancy violations, and that the P3b is not related to the activation of an exclusion-specific neural alarm system. Copyright © 2015 Elsevier B.V. All rights reserved.
Sustained Selective Attention to Competing Amplitude-Modulations in Human Auditory Cortex

PubMed Central

Riecke, Lars; Scharke, Wolfgang; Valente, Giancarlo; Gutschalk, Alexander

2014-01-01

Auditory selective attention plays an essential role for identifying sounds of interest in a scene, but the neural underpinnings are still incompletely understood. Recent findings demonstrate that neural activity that is time-locked to a particular amplitude-modulation (AM) is enhanced in the auditory cortex when the modulated stream of sounds is selectively attended to under sensory competition with other streams. However, the target sounds used in the previous studies differed not only in their AM, but also in other sound features, such as carrier frequency or location. Thus, it remains uncertain whether the observed enhancements reflect AM-selective attention. The present study aims at dissociating the effect of AM frequency on response enhancement in auditory cortex by using an ongoing auditory stimulus that contains two competing targets differing exclusively in their AM frequency. Electroencephalography results showed a sustained response enhancement for auditory attention compared to visual attention, but not for AM-selective attention (attended AM frequency vs. ignored AM frequency). In contrast, the response to the ignored AM frequency was enhanced, although a brief trend toward response enhancement occurred during the initial 15 s. Together with the previous findings, these observations indicate that selective enhancement of attended AMs in auditory cortex is adaptive under sustained AM-selective attention. This finding has implications for our understanding of cortical mechanisms for feature-based attentional gain control. PMID:25259525
Peripheral nerve recruitment curve using near-infrared stimulation

NASA Astrophysics Data System (ADS)

Dautrebande, Marie; Doguet, Pascal; Gorza, Simon-Pierre; Delbeke, Jean; Nonclercq, Antoine

2018-02-01

In the context of near-infrared neurostimulation, we report on an experimental hybrid electrode allowing for simultaneous photonic or electrical neurostimulation and for electrical recording of evoked action potentials. The electrode includes three contacts and one optrode. The optrode is an opening in the cuff through which the tip of an optical fibre is held close to the epineurium. Two contacts provide action potential recording. The remaining contact, together with a remote subcutaneous electrode, is used for electric stimulation which allows periodical assessment of the viability of the nerve during the experiment. A 1470 nm light source was used to stimulate a mouse sciatic nerve. Neural action potentials were not successfully recorded because of the electrical noise so muscular activity was used to reflect the motor fibres stimulation. A recruitment curve was obtained by stimulating with photonic pulses of same power and increasing duration and recording the evoked muscular action potentials. Motor fibres can be recruited with radiant exposures between 0.05 and 0.23 J/cm2 for pulses in the 100 to 500 μs range. Successful stimulation at short duration and at a commercial wavelength is encouraging in the prospect of miniaturisation and practical applications. Motor fibres recruitment curve is a first step in an ongoing research work. Neural action potential acquisition will be improved, with aim to shed light on the mechanism of action potential initiation under photonic stimulation.
Reversal learning as a measure of impulsive and compulsive behavior in addictions.

PubMed

Izquierdo, Alicia; Jentsch, J David

2012-01-01

Our ability to measure the cognitive components of complex decision-making across species has greatly facilitated our understanding of its neurobiological mechanisms. One task in particular, reversal learning, has proven valuable in assessing the inhibitory processes that are central to executive control. Reversal learning measures the ability to actively suppress reward-related responding and to disengage from ongoing behavior, phenomena that are biologically and descriptively related to impulsivity and compulsivity. Consequently, reversal learning could index vulnerability for disorders characterized by impulsivity such as proclivity for initial substance abuse as well as the compulsive aspects of dependence. Though we describe common variants and similar tasks, we pay particular attention to discrimination reversal learning, its supporting neural circuitry, neuropharmacology and genetic determinants. We also review the utility of this task in measuring impulsivity and compulsivity in addictions. We restrict our review to instrumental, reward-related reversal learning studies as they are most germane to addiction. The research reviewed here suggests that discrimination reversal learning may be used as a diagnostic tool for investigating the neural mechanisms that mediate impulsive and compulsive aspects of pathological reward-seeking and -taking behaviors. Two interrelated mechanisms are posited for the neuroadaptations in addiction that often translate to poor reversal learning: frontocorticostriatal circuitry dysregulation and poor dopamine (D2 receptor) modulation of this circuitry. These data suggest new approaches to targeting inhibitory control mechanisms in addictions.

Overcoming residual interference in mental set switching: Neural correlates and developmental trajectory

PubMed Central

Witt, Suzanne T.; Stevens, Michael C.

2012-01-01

Mental set switching is a key facet of executive control measured behaviorally through reaction time or accuracy (i.e., ‘switch costs’) when shifting among task types. One of several experimentally-dissociable influences on switch costs is ‘task set inertia’, conceptualized as the residual interference conferred when a previous stimulus-response tendency interferes with subsequent stimulus processing on a new task. Task set inertia is thought to represent the passive decay of the previous stimulus-response set from working memory, and its effects decrease with increased interstimulus interval. Closely spaced trials confer high task set inertia, while sparsely spaced trials confer low task set inertia. This functional magnetic resonance imaging (fMRI) study characterized, for the first time, two opposing brain systems engaged to resolve task set inertia: 1) a frontoparietal ‘cortical control’ network for overcoming high task set inertia interference and 2) a subcortical-motor network more active during trials with low task set inertia. These networks were distinct from brain regions showing general switching effects (i.e., switch > non-switch) and from other previously-characterized interference effects. Moreover, there were ongoing maturational effects throughout adolescence for the brain regions engaged to overcome high task set inertia not seen for generalized switching effects. These novel findings represent a new avenue of exploration of cognitive set switching neural function. PMID:22584223
Parietal stimulation destabilizes spatial updating across saccadic eye movements.

PubMed

Morris, Adam P; Chambers, Christopher D; Mattingley, Jason B

2007-05-22

Saccadic eye movements cause sudden and global shifts in the retinal image. Rather than causing confusion, however, eye movements expand our sense of space and detail. In macaques, a stable representation of space is embodied by neural populations in intraparietal cortex that redistribute activity with each saccade to compensate for eye displacement, but little is known about equivalent updating mechanisms in humans. We combined noninvasive cortical stimulation with a double-step saccade task to examine the contribution of two human intraparietal areas to transsaccadic spatial updating. Right hemisphere stimulation over the posterior termination of the intraparietal sulcus (IPSp) broadened and shifted the distribution of second-saccade endpoints, but only when the first-saccade was directed into the contralateral hemifield. By interleaving trials with and without cortical stimulation, we show that the shift in endpoints was caused by an enduring effect of stimulation on neural functioning (e.g., modulation of neuronal gain). By varying the onset time of stimulation, we show that the representation of space in IPSp is updated immediately after the first-saccade. In contrast, stimulation of an adjacent IPS site had no such effects on second-saccades. These experiments suggest that stimulation of IPSp distorts an eye position or displacement signal that updates the representation of space at the completion of a saccade. Such sensory-motor integration in IPSp is crucial for the ongoing control of action, and may contribute to visual stability across saccades.
Evidence-Based Systematic Review: Effects of Neuromuscular Electrical Stimulation on Swallowing and Neural Activation

ERIC Educational Resources Information Center

Clark, Heather; Lazarus, Cathy; Arvedson, Joan; Schooling, Tracy; Frymark, Tobi

2009-01-01

Purpose: To systematically review the literature examining the effects of neuromuscular electrical stimulation (NMES) on swallowing and neural activation. The review was conducted as part of a series examining the effects of oral motor exercises (OMEs) on speech, swallowing, and neural activation. Method: A systematic search was conducted to…
An Activity for Demonstrating the Concept of a Neural Circuit

ERIC Educational Resources Information Center

Kreiner, David S.

2012-01-01

College students in two sections of a general psychology course participated in a demonstration of a simple neural circuit. The activity was based on a neural circuit that Jeffress proposed for localizing sounds. Students in one section responded to a questionnaire prior to participating in the activity, while students in the other section…
Mapping of Courtship Behavior-Induced Neural Activity in the Thoracic Ganglia of Silkmoth Bombyx mori by an Immediate Early Gene, Hr38.

PubMed

Morishita, Koudai; Iwami, Masafumi; Kiya, Taketoshi

2018-06-01

In the central nervous system of insects, motor patterns are generated in the thoracic ganglia under the control of brain, where sensory information is integrated and behavioral decisions are made. Previously, we established neural activity-mapping methods using an immediate early gene, BmHr38, as a neural activity marker in the brain of male silkmoth Bombyx mori. In the present study, to gain insights into neural mechanisms of motor-pattern generation in the thoracic ganglia, we investigated expression of BmHr38 in response to sex pheromone-induced courtship behavior. Levels of BmHr38 expression were strongly correlated between the brain and thoracic ganglia, suggesting that neural activity in the thoracic ganglia is tightly controlled by the brain. In situ hybridization of BmHr38 revealed that 20-30% of thoracic neurons are activated by courtship behavior. Using serial sections, we constructed a comprehensive map of courtship behaviorinduced activity in the thoracic ganglia. These results provide important clues into how complex courtship behavior is generated in the neural circuits of thoracic ganglia.
A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control

PubMed Central

Li, Lin; Brockmeier, Austin J.; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

2014-01-01

Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569
Spatiotemporal Imaging of Glutamate-Induced Biophotonic Activities and Transmission in Neural Circuits

PubMed Central

Tang, Rendong; Dai, Jiapei

2014-01-01

The processing of neural information in neural circuits plays key roles in neural functions. Biophotons, also called ultra-weak photon emissions (UPE), may play potential roles in neural signal transmission, contributing to the understanding of the high functions of nervous system such as vision, learning and memory, cognition and consciousness. However, the experimental analysis of biophotonic activities (emissions) in neural circuits has been hampered due to technical limitations. Here by developing and optimizing an in vitro biophoton imaging method, we characterize the spatiotemporal biophotonic activities and transmission in mouse brain slices. We show that the long-lasting application of glutamate to coronal brain slices produces a gradual and significant increase of biophotonic activities and achieves the maximal effect within approximately 90 min, which then lasts for a relatively long time (>200 min). The initiation and/or maintenance of biophotonic activities by glutamate can be significantly blocked by oxygen and glucose deprivation, together with the application of a cytochrome c oxidase inhibitor (sodium azide), but only partly by an action potential inhibitor (TTX), an anesthetic (procaine), or the removal of intracellular and extracellular Ca2+. We also show that the detected biophotonic activities in the corpus callosum and thalamus in sagittal brain slices mostly originate from axons or axonal terminals of cortical projection neurons, and that the hyperphosphorylation of microtubule-associated protein tau leads to a significant decrease of biophotonic activities in these two areas. Furthermore, the application of glutamate in the hippocampal dentate gyrus results in increased biophotonic activities in its intrahippocampal projection areas. These results suggest that the glutamate-induced biophotonic activities reflect biophotonic transmission along the axons and in neural circuits, which may be a new mechanism for the processing of neural information. PMID:24454909
Spatiotemporal imaging of glutamate-induced biophotonic activities and transmission in neural circuits.

PubMed

Tang, Rendong; Dai, Jiapei

2014-01-01

The processing of neural information in neural circuits plays key roles in neural functions. Biophotons, also called ultra-weak photon emissions (UPE), may play potential roles in neural signal transmission, contributing to the understanding of the high functions of nervous system such as vision, learning and memory, cognition and consciousness. However, the experimental analysis of biophotonic activities (emissions) in neural circuits has been hampered due to technical limitations. Here by developing and optimizing an in vitro biophoton imaging method, we characterize the spatiotemporal biophotonic activities and transmission in mouse brain slices. We show that the long-lasting application of glutamate to coronal brain slices produces a gradual and significant increase of biophotonic activities and achieves the maximal effect within approximately 90 min, which then lasts for a relatively long time (>200 min). The initiation and/or maintenance of biophotonic activities by glutamate can be significantly blocked by oxygen and glucose deprivation, together with the application of a cytochrome c oxidase inhibitor (sodium azide), but only partly by an action potential inhibitor (TTX), an anesthetic (procaine), or the removal of intracellular and extracellular Ca(2+). We also show that the detected biophotonic activities in the corpus callosum and thalamus in sagittal brain slices mostly originate from axons or axonal terminals of cortical projection neurons, and that the hyperphosphorylation of microtubule-associated protein tau leads to a significant decrease of biophotonic activities in these two areas. Furthermore, the application of glutamate in the hippocampal dentate gyrus results in increased biophotonic activities in its intrahippocampal projection areas. These results suggest that the glutamate-induced biophotonic activities reflect biophotonic transmission along the axons and in neural circuits, which may be a new mechanism for the processing of neural information.
Cortical thickness in adolescent marijuana and alcohol users: A three-year prospective study from adolescence to young adulthood.

PubMed

Jacobus, Joanna; Squeglia, Lindsay M; Meruelo, Alejandro D; Castro, Norma; Brumback, Ty; Giedd, Jay N; Tapert, Susan F

2015-12-01

Studies suggest marijuana impacts gray and white matter neural tissue development, however few prospective studies have determined the relationship between cortical thickness and cannabis use spanning adolescence to young adulthood. This study aimed to understand how heavy marijuana use influences cortical thickness trajectories across adolescence. Subjects were adolescents with heavy marijuana use and concomitant alcohol use (MJ+ALC, n=30) and controls (CON, n=38) with limited substance use histories. Participants underwent magnetic resonance imaging and comprehensive substance use assessment at three independent time points. Repeated measures analysis of covariance was used to look at main effects of group, time, and Group × Time interactions on cortical thickness. MJ+ALC showed thicker cortical estimates across the brain (23 regions), particularly in frontal and parietal lobes (ps<.05). More cumulative marijuana use was associated with increased thickness estimates by 3-year follow-up (ps<.05). Heavy marijuana use during adolescence and into young adulthood may be associated with altered neural tissue development and interference with neuromaturation that can have neurobehavioral consequences. Continued follow-up of adolescent marijuana users will help understand ongoing neural changes that are associated with development of problematic use into adulthood, as well as potential for neural recovery with cessation of use. Published by Elsevier Ltd.
Evolving a Neural Olfactorimotor System in Virtual and Real Olfactory Environments

PubMed Central

Rhodes, Paul A.; Anderson, Todd O.

2012-01-01

To provide a platform to enable the study of simulated olfactory circuitry in context, we have integrated a simulated neural olfactorimotor system with a virtual world which simulates both computational fluid dynamics as well as a robotic agent capable of exploring the simulated plumes. A number of the elements which we developed for this purpose have not, to our knowledge, been previously assembled into an integrated system, including: control of a simulated agent by a neural olfactorimotor system; continuous interaction between the simulated robot and the virtual plume; the inclusion of multiple distinct odorant plumes and background odor; the systematic use of artificial evolution driven by olfactorimotor performance (e.g., time to locate a plume source) to specify parameter values; the incorporation of the realities of an imperfect physical robot using a hybrid model where a physical robot encounters a simulated plume. We close by describing ongoing work toward engineering a high dimensional, reversible, low power electronic olfactory sensor which will allow olfactorimotor neural circuitry evolved in the virtual world to control an autonomous olfactory robot in the physical world. The platform described here is intended to better test theories of olfactory circuit function, as well as provide robust odor source localization in realistic environments. PMID:23112772
The neural signature of emotional memories in serial crimes.

PubMed

Chassy, Philippe

2017-10-01

Neural plasticity is the process whereby semantic information and emotional responses are stored in neural networks. It is hypothesized that the neural networks built over time to encode the sexual fantasies that motivate serial killers to act should display a unique, detectable activation pattern. The pathological neural watermark hypothesis posits that such networks comprise activation of brain sites that reflect four cognitive components: autobiographical memory, sexual arousal, aggression, and control over aggression. The neural sites performing these cognitive functions have been successfully identified by previous research. The key findings are reviewed to hypothesise the typical pattern of activity that serial killers should display. Through the integration of biological findings into one framework, the neural approach proposed in this paper is in stark contrast with the many theories accounting for serial killers that offer non-medical taxonomies. The pathological neural watermark hypothesis offers a new framework to understand and detect deviant individuals. The technical and legal issues are briefly discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.
24 CFR 35.1220 - Ongoing lead-based paint maintenance activities.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 24 Housing and Urban Development 1 2014-04-01 2014-04-01 false Ongoing lead-based paint..., Department of Housing and Urban Development LEAD-BASED PAINT POISONING PREVENTION IN CERTAIN RESIDENTIAL STRUCTURES Tenant-Based Rental Assistance § 35.1220 Ongoing lead-based paint maintenance activities...
24 CFR 35.1220 - Ongoing lead-based paint maintenance activities.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 24 Housing and Urban Development 1 2012-04-01 2012-04-01 false Ongoing lead-based paint..., Department of Housing and Urban Development LEAD-BASED PAINT POISONING PREVENTION IN CERTAIN RESIDENTIAL STRUCTURES Tenant-Based Rental Assistance § 35.1220 Ongoing lead-based paint maintenance activities...
24 CFR 35.1220 - Ongoing lead-based paint maintenance activities.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 24 Housing and Urban Development 1 2011-04-01 2011-04-01 false Ongoing lead-based paint..., Department of Housing and Urban Development LEAD-BASED PAINT POISONING PREVENTION IN CERTAIN RESIDENTIAL STRUCTURES Tenant-Based Rental Assistance § 35.1220 Ongoing lead-based paint maintenance activities...
24 CFR 35.1220 - Ongoing lead-based paint maintenance activities.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 24 Housing and Urban Development 1 2013-04-01 2013-04-01 false Ongoing lead-based paint..., Department of Housing and Urban Development LEAD-BASED PAINT POISONING PREVENTION IN CERTAIN RESIDENTIAL STRUCTURES Tenant-Based Rental Assistance § 35.1220 Ongoing lead-based paint maintenance activities...
24 CFR 35.1220 - Ongoing lead-based paint maintenance activities.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 24 Housing and Urban Development 1 2010-04-01 2010-04-01 false Ongoing lead-based paint..., Department of Housing and Urban Development LEAD-BASED PAINT POISONING PREVENTION IN CERTAIN RESIDENTIAL STRUCTURES Tenant-Based Rental Assistance § 35.1220 Ongoing lead-based paint maintenance activities...
Habit strength is predicted by activity dynamics in goal-directed brain systems during training.

PubMed

Zwosta, Katharina; Ruge, Hannes; Goschke, Thomas; Wolfensteller, Uta

2018-01-15

Previous neuroscientific research revealed insights into the brain networks supporting goal-directed and habitual behavior, respectively. However, it remains unclear how these contribute to inter-individual differences in habit strength which is relevant for understanding not only normal behavior but also more severe dysregulations between these types of action control, such as in addiction. In the present fMRI study, we trained subjects on approach and avoidance behavior for an extended period of time before testing the habit strength of the acquired stimulus-response associations. We found that stronger habits were associated with a stronger decrease in inferior parietal lobule activity for approach and avoidance behavior and weaker vmPFC activity at the end of training for avoidance behavior, areas associated with the anticipation of outcome identity and value. VmPFC in particular showed markedly different activity dynamics during the training of approach and avoidance behavior. Furthermore, while ongoing training was accompanied by increasing functional connectivity between posterior putamen and premotor cortex, consistent with previous assumptions about the neural basis of increasing habitualization, this was not predictive of later habit strength. Together, our findings suggest that inter-individual differences in habitual behavior are driven by differences in the persistent involvement of brain areas supporting goal-directed behavior during training. Copyright © 2017. Published by Elsevier Inc.
Increased Neural Activation during Picture Encoding and Retrieval in 60-Year-Olds Compared to 20-Year-Olds

ERIC Educational Resources Information Center

Burgmans, S.; van Boxtel, M. P. J.; Vuurman, E. F. P. M.; Evers, E. A. T.; Jolles, J.

2010-01-01

Brain aging has been associated with both reduced and increased neural activity during task execution. The purpose of the present study was to investigate whether increased neural activation during memory encoding and retrieval is already present at the age of 60 as well as to obtain more insight into the mechanism behind increased activity.…
Patterns of work attitudes: A neural network approach

NASA Astrophysics Data System (ADS)

Mengov, George D.; Zinovieva, Irina L.; Sotirov, George R.

2000-05-01

In this paper we introduce a neural networks based approach to analyzing empirical data and models from work and organizational psychology (WOP), and suggest possible implications for the practice of managers and business consultants. With this method it becomes possible to have quantitative answers to a bunch of questions like: What are the characteristics of an organization in terms of its employees' motivation? What distinct attitudes towards the work exist? Which pattern is most desirable from the standpoint of productivity and professional achievement? What will be the dynamics of behavior as quantified by our method, during an ongoing organizational change or consultancy intervention? Etc. Our investigation is founded on the theoretical achievements of Maslow (1954, 1970) in human motivation, and of Hackman & Oldham (1975, 1980) in job diagnostics, and applies the mathematical algorithm of the dARTMAP variation (Carpenter et al., 1998) of the Adaptive Resonance Theory (ART) neural networks introduced by Grossberg (1976). We exploit the ART capabilities to visualize the knowledge accumulated in the network's long-term memory in order to interpret the findings in organizational research.
Bio-behavioral synchrony promotes the development of conceptualized emotions.

PubMed

Atzil, Shir; Gendron, Maria

2017-10-01

As adults, we have structured conceptual representations of our emotions that help us to make sense of and regulate our ongoing affective experience. The ability to use emotion concepts is critical to make predictions about the world and choose appropriate action, such as 'I am afraid, and going to run away' or 'I am hungry and going to eat'. Thus, emotion concepts have an important role in helping us maintain our ongoing physiological balance, or allostasis. We will suggest here that infants can learn emotion concepts for the purpose of allostasis regulation, and that conceptualization is key component in emotional development. Moreover, we will suggest that social dyads facilitate concept learning because of a robust evolutionary feature seen in newborns of social species: they cannot survive alone and depend on conspecifics for allostasis regulation. Such social dependency creates a robust driving force for social learning of emotion concepts, and makes the social dyad, which is designed to regulate the infant's allostasis, an optimal medium for concept learning. In line with that, we will review evidence showing that the neural reference space for emotion overlaps with neural circuits that support allostasis (striatum, amygdala, and hypothalamus) and conceptualization (medial prefrontal cortex, posterior cingulate cortex), and that their developmental trajectories are interrelated, and depend on synchronous social care. Copyright © 2017 Elsevier Ltd. All rights reserved.

Inhibition of Excessive Monoamine Oxidase A/B Activity Protects Against Stress-induced Neuronal Death in Huntington Disease.

PubMed

Ooi, Jolene; Hayden, Michael R; Pouladi, Mahmoud A

2015-12-01

Monoamine oxidases (MAO) are important components of the homeostatic machinery that maintains the levels of monoamine neurotransmitters, including dopamine, in balance. Given the imbalance in dopamine levels observed in Huntington disease (HD), the aim of this study was to examine MAO activity in a mouse striatal cell model of HD and in human neural cells differentiated from control and HD patient-derived induced pluripotent stem cell (hiPSC) lines. We show that mouse striatal neural cells expressing mutant huntingtin (HTT) exhibit increased MAO expression and activity. We demonstrate using luciferase promoter assays that the increased MAO expression reflects enhanced epigenetic activation in striatal neural cells expressing mutant HTT. Using cellular stress paradigms, we further demonstrate that the increase in MAO activity in mutant striatal neural cells is accompanied by enhanced susceptibility to oxidative stress and impaired viability. Treatment of mutant striatal neural cells with MAO inhibitors ameliorated oxidative stress and improved cellular viability. Finally, we demonstrate that human HD neural cells exhibit increased MAO-A and MAO-B expression and activity. Altogether, this study demonstrates abnormal MAO expression and activity and suggests a potential use for MAO inhibitors in HD.
Italy between drinking culture and control policies for alcoholic beverages.

PubMed

Allamani, Allaman; Voller, Fabio; Pepe, Pasquale; Baccini, Michela; Massini, Giulia; Cipriani, Francesco

2014-10-01

This paper focuses on whether the on-going dramatic decrease in alcohol consumption in Italy, especially of wine, during 1961-2008, was associated with which parallel sociodemographic and economic changes and with alcohol control policies. The study, using both time series (TS) and artificial neural network (ANN)-based analyses documents that its selected sociodemographic and economic factors, and particularly urbanization, had a definite connection with wine consumption decrease, spirits decrease, and the increase in beer consumption over time. On the other hand, control policies showed no effect on the decline in alcohol consumption, since no alcohol control policy existed in Italy between 1960 and 1987. A few policies introduced since 1988 (BAC and sale restrictions during mass events) may have contributed to reducing or to maintaining the on-going reduction. Study limitations are noted and future needed research is suggested.
Regulation of Msx genes by a Bmp gradient is essential for neural crest specification.

PubMed

Tribulo, Celeste; Aybar, Manuel J; Nguyen, Vu H; Mullins, Mary C; Mayor, Roberto

2003-12-01

There is evidence in Xenopus and zebrafish embryos that the neural crest/neural folds are specified at the border of the neural plate by a precise threshold concentration of a Bmp gradient. In order to understand the molecular mechanism by which a gradient of Bmp is able to specify the neural crest, we analyzed how the expression of Bmp targets, the Msx genes, is regulated and the role that Msx genes has in neural crest specification. As Msx genes are directly downstream of Bmp, we analyzed Msx gene expression after experimental modification in the level of Bmp activity by grafting a bead soaked with noggin into Xenopus embryos, by expressing in the ectoderm a dominant-negative Bmp4 or Bmp receptor in Xenopus and zebrafish embryos, and also through Bmp pathway component mutants in the zebrafish. All the results show that a reduction in the level of Bmp activity leads to an increase in the expression of Msx genes in the neural plate border. Interestingly, by reaching different levels of Bmp activity in animal cap ectoderm, we show that a specific concentration of Bmp induces msx1 expression to a level similar to that required to induce neural crest. Our results indicate that an intermediate level of Bmp activity specifies the expression of Msx genes in the neural fold region. In addition, we have analyzed the role that msx1 plays on neural crest specification. As msx1 has a role in dorsoventral pattering, we have carried out conditional gain- and loss-of-function experiments using different msx1 constructs fused to a glucocorticoid receptor element to avoid an early effect of this factor. We show that msx1 expression is able to induce all other early neural crest markers tested (snail, slug, foxd3) at the time of neural crest specification. Furthermore, the expression of a dominant negative of Msx genes leads to the inhibition of all the neural crest markers analyzed. It has been previously shown that snail is one of the earliest genes acting in the neural crest genetic cascade. In order to study the hierarchical relationship between msx1 and snail/slug we performed several rescue experiments using dominant negatives for these genes. The rescuing activity by snail and slug on neural crest development of the msx1 dominant negative, together with the inability of msx1 to rescue the dominant negatives of slug and snail strongly argue that msx1 is upstream of snail and slug in the genetic cascade that specifies the neural crest in the ectoderm. We propose a model where a gradient of Bmp activity specifies the expression of Msx genes in the neural folds, and that this expression is essential for the early specification of the neural crest.
24 CFR 35.935 - Ongoing lead-based paint maintenance activities.

Code of Federal Regulations, 2011 CFR

2011-04-01

..., Department of Housing and Urban Development LEAD-BASED PAINT POISONING PREVENTION IN CERTAIN RESIDENTIAL STRUCTURES Rehabilitation § 35.935 Ongoing lead-based paint maintenance activities. In the case of a rental... 24 Housing and Urban Development 1 2011-04-01 2011-04-01 false Ongoing lead-based paint...
24 CFR 35.935 - Ongoing lead-based paint maintenance activities.

Code of Federal Regulations, 2012 CFR

2012-04-01

..., Department of Housing and Urban Development LEAD-BASED PAINT POISONING PREVENTION IN CERTAIN RESIDENTIAL STRUCTURES Rehabilitation § 35.935 Ongoing lead-based paint maintenance activities. In the case of a rental... 24 Housing and Urban Development 1 2012-04-01 2012-04-01 false Ongoing lead-based paint...
24 CFR 35.935 - Ongoing lead-based paint maintenance activities.

Code of Federal Regulations, 2014 CFR

2014-04-01

..., Department of Housing and Urban Development LEAD-BASED PAINT POISONING PREVENTION IN CERTAIN RESIDENTIAL STRUCTURES Rehabilitation § 35.935 Ongoing lead-based paint maintenance activities. In the case of a rental... 24 Housing and Urban Development 1 2014-04-01 2014-04-01 false Ongoing lead-based paint...
24 CFR 35.935 - Ongoing lead-based paint maintenance activities.

Code of Federal Regulations, 2010 CFR

2010-04-01

..., Department of Housing and Urban Development LEAD-BASED PAINT POISONING PREVENTION IN CERTAIN RESIDENTIAL STRUCTURES Rehabilitation § 35.935 Ongoing lead-based paint maintenance activities. In the case of a rental... 24 Housing and Urban Development 1 2010-04-01 2010-04-01 false Ongoing lead-based paint...
24 CFR 35.935 - Ongoing lead-based paint maintenance activities.

Code of Federal Regulations, 2013 CFR

2013-04-01

..., Department of Housing and Urban Development LEAD-BASED PAINT POISONING PREVENTION IN CERTAIN RESIDENTIAL STRUCTURES Rehabilitation § 35.935 Ongoing lead-based paint maintenance activities. In the case of a rental... 24 Housing and Urban Development 1 2013-04-01 2013-04-01 false Ongoing lead-based paint...
Increasing Spontaneous Retinal Activity before Eye Opening Accelerates the Development of Geniculate Receptive Fields

PubMed Central

Davis, Zachary W.; Chapman, Barbara

2015-01-01

Visually evoked activity is necessary for the normal development of the visual system. However, little is known about the capacity for patterned spontaneous activity to drive the maturation of receptive fields before visual experience. Retinal waves provide instructive retinotopic information for the anatomical organization of the visual thalamus. To determine whether retinal waves also drive the maturation of functional responses, we increased the frequency of retinal waves pharmacologically in the ferret (Mustela putorius furo) during a period of retinogeniculate development before eye opening. The development of geniculate receptive fields after receiving these increased neural activities was measured using single-unit electrophysiology. We found that increased retinal waves accelerate the developmental reduction of geniculate receptive field sizes. This reduction is due to a decrease in receptive field center size rather than an increase in inhibitory surround strength. This work reveals an instructive role for patterned spontaneous activity in guiding the functional development of neural circuits. SIGNIFICANCE STATEMENT Patterned spontaneous neural activity that occurs during development is known to be necessary for the proper formation of neural circuits. However, it is unknown whether the spontaneous activity alone is sufficient to drive the maturation of the functional properties of neurons. Our work demonstrates for the first time an acceleration in the maturation of neural function as a consequence of driving patterned spontaneous activity during development. This work has implications for our understanding of how neural circuits can be modified actively to improve function prematurely or to recover from injury with guided interventions of patterned neural activity. PMID:26511250
Neural Correlates of Moral Sensitivity and Moral Judgment Associated with Brain Circuitries of Selfhood: A Meta-Analysis

ERIC Educational Resources Information Center

Han, Hyemin

2017-01-01

The present study meta-analyzed 45 experiments with 959 subjects and 463 activation foci reported in 43 published articles that investigated the neural mechanism of moral functions by comparing neural activity between the moral task conditions and non-moral task conditions with the Activation Likelihood Estimation method. The present study…
Distinguishing Adolescents With ADHD From Their Unaffected Siblings and Healthy Comparison Subjects by Neural Activation Patterns During Response Inhibition.

PubMed

van Rooij, Daan; Hoekstra, Pieter J; Mennes, Maarten; von Rhein, Daniel; Thissen, Andrieke J A M; Heslenfeld, Dirk; Zwiers, Marcel P; Faraone, Stephen V; Oosterlaan, Jaap; Franke, Barbara; Rommelse, Nanda; Buitelaar, Jan K; Hartman, Catharina A

2015-07-01

Dysfunctional response inhibition is a key executive function impairment in attention deficit hyperactivity disorder (ADHD). Still, behavioral response inhibition measures do not consistently differentiate affected from unaffected individuals. The authors therefore investigated neural correlates of response inhibition and the familial nature of these neural correlates. Functional MRI measurements of neural activation during the stop-signal task and behavioral measures of response inhibition were obtained in adolescents and young adults with ADHD (N=185), their unaffected siblings (N=111), and healthy comparison subjects (N=124). Stop-signal task reaction times were longer and error rates were higher in participants with ADHD, but not in their unaffected siblings, while reaction time variability was higher in both groups than in comparison subjects. Relative to comparison subjects, participants with ADHD and unaffected siblings had neural hypoactivation in frontal-striatal and frontal-parietal networks, whereby activation in inferior frontal and temporal/parietal nodes in unaffected siblings was intermediate between levels of participants with ADHD and comparison subjects. Furthermore, neural activation in inferior frontal nodes correlated with stop-signal reaction times, and activation in both inferior frontal and temporal/parietal nodes correlated with ADHD severity. Neural activation alterations in ADHD are more robust than behavioral response inhibition deficits and explain variance in response inhibition and ADHD severity. Although only affected participants with ADHD have deficient response inhibition, hypoactivation in inferior frontal and temporal-parietal nodes in unaffected siblings supports the familial nature of the underlying neural process. Activation deficits in these nodes may be useful as endophenotypes that extend beyond the affected individuals in the family.
Neural circuits via which single prolonged stress exposure leads to fear extinction retention deficits.

PubMed

Knox, Dayan; Stanfield, Briana R; Staib, Jennifer M; David, Nina P; Keller, Samantha M; DePietro, Thomas

2016-12-01

Single prolonged stress (SPS) has been used to examine mechanisms via which stress exposure leads to post-traumatic stress disorder symptoms. SPS induces fear extinction retention deficits, but neural circuits critical for mediating these deficits are unknown. To address this gap, we examined the effect of SPS on neural activity in brain regions critical for extinction retention (i.e., fear extinction circuit). These were the ventral hippocampus (vHipp), dorsal hippocampus (dHipp), basolateral amygdala (BLA), prelimbic cortex (PL), and infralimbic cortex (IL). SPS or control rats were fear conditioned then subjected to extinction training and testing. Subsets of rats were euthanized after extinction training, extinction testing, or immediate removal from the housing colony (baseline condition) to assay c-Fos levels (measure of neural activity) in respective brain region. SPS induced extinction retention deficits. During extinction training SPS disrupted enhanced IL neural activity and inhibited BLA neural activity. SPS also disrupted inhibited BLA and vHipp neural activity during extinction testing. Statistical analyses suggested that SPS disrupted functional connectivity within the dHipp during extinction training and increased functional connectivity between the BLA and vHipp during extinction testing. Our findings suggest that SPS induces extinction retention deficits by disrupting both excitatory and inhibitory changes in neural activity within the fear extinction circuit and inducing changes in functional connectivity within the Hipp and BLA. © 2016 Knox et al.; Published by Cold Spring Harbor Laboratory Press.
Automated target recognition and tracking using an optical pattern recognition neural network

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

1991-01-01

The on-going development of an automatic target recognition and tracking system at the Jet Propulsion Laboratory is presented. This system is an optical pattern recognition neural network (OPRNN) that is an integration of an innovative optical parallel processor and a feature extraction based neural net training algorithm. The parallel optical processor provides high speed and vast parallelism as well as full shift invariance. The neural network algorithm enables simultaneous discrimination of multiple noisy targets in spite of their scales, rotations, perspectives, and various deformations. This fully developed OPRNN system can be effectively utilized for the automated spacecraft recognition and tracking that will lead to success in the Automated Rendezvous and Capture (AR&C) of the unmanned Cargo Transfer Vehicle (CTV). One of the most powerful optical parallel processors for automatic target recognition is the multichannel correlator. With the inherent advantages of parallel processing capability and shift invariance, multiple objects can be simultaneously recognized and tracked using this multichannel correlator. This target tracking capability can be greatly enhanced by utilizing a powerful feature extraction based neural network training algorithm such as the neocognitron. The OPRNN, currently under investigation at JPL, is constructed with an optical multichannel correlator where holographic filters have been prepared using the neocognitron training algorithm. The computation speed of the neocognitron-type OPRNN is up to 10(exp 14) analog connections/sec that enabling the OPRNN to outperform its state-of-the-art electronics counterpart by at least two orders of magnitude.
Neural Activity in the Ventral Pallidum Encodes Variation in the Incentive Value of a Reward Cue.

PubMed

Ahrens, Allison M; Meyer, Paul J; Ferguson, Lindsay M; Robinson, Terry E; Aldridge, J Wayne

2016-07-27

There is considerable individual variation in the extent to which reward cues are attributed with incentive salience. For example, a food-predictive conditioned stimulus (CS; an illuminated lever) becomes attractive, eliciting approach toward it only in some rats ("sign trackers," STs), whereas others ("goal trackers," GTs) approach the food cup during the CS period. The purpose of this study was to determine how individual differences in Pavlovian approach responses are represented in neural firing patterns in the major output structure of the mesolimbic system, the ventral pallidum (VP). Single-unit in vivo electrophysiology was used to record neural activity in the caudal VP during the performance of ST and GT conditioned responses. All rats showed neural responses to both cue onset and reward delivery but, during the CS period, STs showed greater neural activity than GTs both in terms of the percentage of responsive neurons and the magnitude of the change in neural activity. Furthermore, neural activity was positively correlated with the degree of attraction to the cue. Given that the CS had equal predictive value in STs and GTs, we conclude that neural activity in the VP largely reflects the degree to which the CS was attributed with incentive salience. Cues associated with reward can acquire motivational properties (i.e., incentive salience) that cause them to have a powerful influence on desire and motivated behavior. There are individual differences in sensitivity to reward-paired cues, with some individuals attaching greater motivational value to cues than others. Here, we investigated the neural activity associated with these individual differences in incentive salience. We found that cue-evoked neural firing in the ventral pallidum (VP) reflected the strength of incentive motivation, with the greatest neural responses occurring in individuals that demonstrated the strongest attraction to the cue. This suggests that the VP plays an important role in the process by which cues gain control over motivation and behavior. Copyright © 2016 the authors 0270-6474/16/367957-14$15.00/0.
Cognitive emotion regulation in children: Reappraisal of emotional faces modulates neural source activity in a frontoparietal network.

PubMed

Wessing, Ida; Rehbein, Maimu A; Romer, Georg; Achtergarde, Sandra; Dobel, Christian; Zwitserlood, Pienie; Fürniss, Tilman; Junghöfer, Markus

2015-06-01

Emotion regulation has an important role in child development and psychopathology. Reappraisal as cognitive regulation technique can be used effectively by children. Moreover, an ERP component known to reflect emotional processing called late positive potential (LPP) can be modulated by children using reappraisal and this modulation is also related to children's emotional adjustment. The present study seeks to elucidate the neural generators of such LPP effects. To this end, children aged 8-14 years reappraised emotional faces, while neural activity in an LPP time window was estimated using magnetoencephalography-based source localization. Additionally, neural activity was correlated with two indexes of emotional adjustment and age. Reappraisal reduced activity in the left dorsolateral prefrontal cortex during down-regulation and enhanced activity in the right parietal cortex during up-regulation. Activity in the visual cortex decreased with increasing age, more adaptive emotion regulation and less anxiety. Results demonstrate that reappraisal changed activity within a frontoparietal network in children. Decreasing activity in the visual cortex with increasing age is suggested to reflect neural maturation. A similar decrease with adaptive emotion regulation and less anxiety implies that better emotional adjustment may be associated with an advance in neural maturation. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Effects of aberrant gamma frequency oscillations on prepulse inhibition.

PubMed

Jones, Nigel C; Anderson, Paul; Rind, Gil; Sullivan, Caley; van den Buuse, Maarten; O'Brien, Terence J

2014-10-01

Emerging literature implicates abnormalities in gamma frequency oscillations in the pathophysiology of schizophrenia, with hypofunction of N-methyl-D-aspartate (NMDA) receptors implicated as a key factor. Prepulse inhibition (PPI) is a behavioural measure of sensorimotor gating, which is disrupted in schizophrenia. We studied relationships between ongoing and sensory-evoked gamma oscillations and PPI using pharmacological interventions designed to increase gamma oscillations (ketamine, MK-801); reduce gamma oscillations (LY379268); or disrupt PPI (amphetamine). We predicted that elevating ongoing gamma power would lead to increased 'neural noise' in cortical circuits, dampened sensory-evoked gamma responses and disrupted behaviour. Wistar rats were implanted with EEG recording electrodes. They received ketamine (5 mg/kg), MK-801 (0.16 mg/kg), amphetamine (0.5 mg/kg), LY379268 (3 mg/kg) or vehicle and underwent PPI sessions with concurrent EEG recording. Ketamine and MK-801 increased the power of ongoing gamma oscillations and caused time-matched disruptions of PPI, while amphetamine marginally affected ongoing gamma power. In contrast, LY379268 reduced ongoing gamma power, but had no effect on PPI. The sensory gamma response evoked by the prepulse was reduced following treatment with all psychotomimetics, associating with disruptions in PPI. This was most noticeable following treatment with NMDA receptor antagonists. We found that ketamine and MK-801 increase ongoing gamma power and reduce evoked gamma power, both of which are related to disruptions in sensorimotor gating. This appears to be due to antagonism of NMDA receptors, since amphetamine and LY379268 differentially impacted these outcomes and possess different neuropharmacological substrates. Aberrant gamma frequency oscillations caused by NMDA receptor hypofunction may mediate the sensory processing deficits observed in schizophrenia.
Improving visual perception through neurofeedback

PubMed Central

Scharnowski, Frank; Hutton, Chloe; Josephs, Oliver; Weiskopf, Nikolaus; Rees, Geraint

2012-01-01

Perception depends on the interplay of ongoing spontaneous activity and stimulus-evoked activity in sensory cortices. This raises the possibility that training ongoing spontaneous activity alone might be sufficient for enhancing perceptual sensitivity. To test this, we trained human participants to control ongoing spontaneous activity in circumscribed regions of retinotopic visual cortex using real-time functional MRI based neurofeedback. After training, we tested participants using a new and previously untrained visual detection task that was presented at the visual field location corresponding to the trained region of visual cortex. Perceptual sensitivity was significantly enhanced only when participants who had previously learned control over ongoing activity were now exercising control, and only for that region of visual cortex. Our new approach allows us to non-invasively and non-pharmacologically manipulate regionally specific brain activity, and thus provide ‘brain training’ to deliver particular perceptual enhancements. PMID:23223302
Neural mechanisms of response inhibition and impulsivity in 22q11.2 deletion carriers and idiopathic attention deficit hyperactivity disorder.

PubMed

Montojo, C A; Congdon, E; Hwang, L; Jalbrzikowski, M; Kushan, L; Vesagas, T K; Jonas, R K; Ventura, J; Bilder, R M; Bearden, C E

2015-01-01

•22q11DS offers a compelling model to understand the neural substrates of attentional dysfunction.•First study directly comparing neural function in 22q11DS vs. ADHD patients•22q11DS and ADHD patients show a shared deficit in RI-related activation.•ADHD patients showed greater activity in the middle frontal gyrus than 22q11DS during RI.•Neural activity is inversely correlated with self-reported Cognitive Impulsivity in 22q11DS.
Spatially Compact Neural Clusters in the Dorsal Striatum Encode Locomotion Relevant Information.

PubMed

Barbera, Giovanni; Liang, Bo; Zhang, Lifeng; Gerfen, Charles R; Culurciello, Eugenio; Chen, Rong; Li, Yun; Lin, Da-Ting

2016-10-05

An influential striatal model postulates that neural activities in the striatal direct and indirect pathways promote and inhibit movement, respectively. Normal behavior requires coordinated activity in the direct pathway to facilitate intended locomotion and indirect pathway to inhibit unwanted locomotion. In this striatal model, neuronal population activity is assumed to encode locomotion relevant information. Here, we propose a novel encoding mechanism for the dorsal striatum. We identified spatially compact neural clusters in both the direct and indirect pathways. Detailed characterization revealed similar cluster organization between the direct and indirect pathways, and cluster activities from both pathways were correlated with mouse locomotion velocities. Using machine-learning algorithms, cluster activities could be used to decode locomotion relevant behavioral states and locomotion velocity. We propose that neural clusters in the dorsal striatum encode locomotion relevant information and that coordinated activities of direct and indirect pathway neural clusters are required for normal striatal controlled behavior. VIDEO ABSTRACT. Published by Elsevier Inc.
Research on image retrieval using deep convolutional neural network combining L1 regularization and PRelu activation function

NASA Astrophysics Data System (ADS)

QingJie, Wei; WenBin, Wang

2017-06-01

In this paper, the image retrieval using deep convolutional neural network combined with regularization and PRelu activation function is studied, and improves image retrieval accuracy. Deep convolutional neural network can not only simulate the process of human brain to receive and transmit information, but also contains a convolution operation, which is very suitable for processing images. Using deep convolutional neural network is better than direct extraction of image visual features for image retrieval. However, the structure of deep convolutional neural network is complex, and it is easy to over-fitting and reduces the accuracy of image retrieval. In this paper, we combine L1 regularization and PRelu activation function to construct a deep convolutional neural network to prevent over-fitting of the network and improve the accuracy of image retrieval

Mdm2 mediates FMRP- and Gp1 mGluR-dependent protein translation and neural network activity.

PubMed

Liu, Dai-Chi; Seimetz, Joseph; Lee, Kwan Young; Kalsotra, Auinash; Chung, Hee Jung; Lu, Hua; Tsai, Nien-Pei

2017-10-15

Activating Group 1 (Gp1) metabotropic glutamate receptors (mGluRs), including mGluR1 and mGluR5, elicits translation-dependent neural plasticity mechanisms that are crucial to animal behavior and circuit development. Dysregulated Gp1 mGluR signaling has been observed in numerous neurological and psychiatric disorders. However, the molecular pathways underlying Gp1 mGluR-dependent plasticity mechanisms are complex and have been elusive. In this study, we identified a novel mechanism through which Gp1 mGluR mediates protein translation and neural plasticity. Using a multi-electrode array (MEA) recording system, we showed that activating Gp1 mGluR elevates neural network activity, as demonstrated by increased spontaneous spike frequency and burst activity. Importantly, we validated that elevating neural network activity requires protein translation and is dependent on fragile X mental retardation protein (FMRP), the protein that is deficient in the most common inherited form of mental retardation and autism, fragile X syndrome (FXS). In an effort to determine the mechanism by which FMRP mediates protein translation and neural network activity, we demonstrated that a ubiquitin E3 ligase, murine double minute-2 (Mdm2), is required for Gp1 mGluR-induced translation and neural network activity. Our data showed that Mdm2 acts as a translation suppressor, and FMRP is required for its ubiquitination and down-regulation upon Gp1 mGluR activation. These data revealed a novel mechanism by which Gp1 mGluR and FMRP mediate protein translation and neural network activity, potentially through de-repressing Mdm2. Our results also introduce an alternative way for understanding altered protein translation and brain circuit excitability associated with Gp1 mGluR in neurological diseases such as FXS. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Periodicity and global exponential stability of generalized Cohen-Grossberg neural networks with discontinuous activations and mixed delays.

PubMed

Wang, Dongshu; Huang, Lihong

2014-03-01

In this paper, we investigate the periodic dynamical behaviors for a class of general Cohen-Grossberg neural networks with discontinuous right-hand sides, time-varying and distributed delays. By means of retarded differential inclusions theory and the fixed point theorem of multi-valued maps, the existence of periodic solutions for the neural networks is obtained. After that, we derive some sufficient conditions for the global exponential stability and convergence of the neural networks, in terms of nonsmooth analysis theory with generalized Lyapunov approach. Without assuming the boundedness (or the growth condition) and monotonicity of the discontinuous neuron activation functions, our results will also be valid. Moreover, our results extend previous works not only on discrete time-varying and distributed delayed neural networks with continuous or even Lipschitz continuous activations, but also on discrete time-varying and distributed delayed neural networks with discontinuous activations. We give some numerical examples to show the applicability and effectiveness of our main results. Copyright © 2013 Elsevier Ltd. All rights reserved.
Targeting Neural Synchrony Deficits is Sufficient to Improve Cognition in a Schizophrenia-Related Neurodevelopmental Model

PubMed Central

Lee, Heekyung; Dvorak, Dino; Fenton, André A.

2014-01-01

Cognitive symptoms are core features of mental disorders but procognitive treatments are limited. We have proposed a “discoordination” hypothesis that cognitive impairment results from aberrant coordination of neural activity. We reported that neonatal ventral hippocampus lesion (NVHL) rats, an established neurodevelopmental model of schizophrenia, have abnormal neural synchrony and cognitive deficits in the active place avoidance task. During stillness, we observed that cortical local field potentials sometimes resembled epileptiform spike-wave discharges with higher prevalence in NVHL rats, indicating abnormal neural synchrony due perhaps to imbalanced excitation–inhibition coupling. Here, within the context of the hypothesis, we investigated whether attenuating abnormal neural synchrony will improve cognition in NVHL rats. We report that: (1) inter-hippocampal synchrony in the theta and beta bands is correlated with active place avoidance performance; (2) the anticonvulsant ethosuximide attenuated the abnormal spike-wave activity, improved cognitive control, and reduced hyperlocomotion; (3) ethosuximide not only normalized the task-associated theta and beta synchrony between the two hippocampi but also increased synchrony between the medial prefrontal cortex and hippocampus above control levels; (4) the antipsychotic olanzapine was less effective at improving cognitive control and normalizing place avoidance-related inter-hippocampal neural synchrony, although it reduced hyperactivity; and (5) olanzapine caused an abnormal pattern of frequency-independent increases in neural synchrony, in both NVHL and control rats. These data suggest that normalizing aberrant neural synchrony can be beneficial and that drugs targeting the pathophysiology of abnormally coordinated neural activities may be a promising theoretical framework and strategy for developing treatments that improve cognition in neurodevelopmental disorders such as schizophrenia. PMID:24592242
Impaired Tuning of Neural Ensembles and the Pathophysiology of Schizophrenia: A Translational and Computational Neuroscience Perspective.

PubMed

Krystal, John H; Anticevic, Alan; Yang, Genevieve J; Dragoi, George; Driesen, Naomi R; Wang, Xiao-Jing; Murray, John D

2017-05-15

The functional optimization of neural ensembles is central to human higher cognitive functions. When the functions through which neural activity is tuned fail to develop or break down, symptoms and cognitive impairments arise. This review considers ways in which disturbances in the balance of excitation and inhibition might develop and be expressed in cortical networks in association with schizophrenia. This presentation is framed within a developmental perspective that begins with disturbances in glutamate synaptic development in utero. It considers developmental correlates and consequences, including compensatory mechanisms that increase intrinsic excitability or reduce inhibitory tone. It also considers the possibility that these homeostatic increases in excitability have potential negative functional and structural consequences. These negative functional consequences of disinhibition may include reduced working memory-related cortical activity associated with the downslope of the "inverted-U" input-output curve, impaired spatial tuning of neural activity and impaired sparse coding of information, and deficits in the temporal tuning of neural activity and its implication for neural codes. The review concludes by considering the functional significance of noisy activity for neural network function. The presentation draws on computational neuroscience and pharmacologic and genetic studies in animals and humans, particularly those involving N-methyl-D-aspartate glutamate receptor antagonists, to illustrate principles of network regulation that give rise to features of neural dysfunction associated with schizophrenia. While this presentation focuses on schizophrenia, the general principles outlined in the review may have broad implications for considering disturbances in the regulation of neural ensembles in psychiatric disorders. Published by Elsevier Inc.
Longitudinal relationships among activity in attention redirection neural circuitry and symptom severity in youth.

PubMed

Bertocci, Michele A; Bebko, Genna; Dwojak, Amanda; Iyengar, Satish; Ladouceur, Cecile D; Fournier, Jay C; Versace, Amelia; Perlman, Susan B; Almeida, Jorge R C; Travis, Michael J; Gill, Mary Kay; Bonar, Lisa; Schirda, Claudiu; Diwadkar, Vaibhav A; Sunshine, Jeffrey L; Holland, Scott K; Kowatch, Robert A; Birmaher, Boris; Axelson, David; Horwitz, Sarah M; Frazier, Thomas; Arnold, L Eugene; Fristad, Mary A; Youngstrom, Eric A; Findling, Robert L; Phillips, Mary L

2017-05-01

Changes in neural circuitry function may be associated with longitudinal changes in psychiatric symptom severity. Identification of these relationships may aid in elucidating the neural basis of psychiatric symptom evolution over time. We aimed to distinguish these relationships using data from the Longitudinal Assessment of Manic Symptoms (LAMS) cohort. Forty-one youth completed two study visits (mean=21.3 months). Elastic-net regression (Multiple response Gaussian family) identified emotional regulation neural circuitry that changed in association with changes in depression, mania, anxiety, affect lability, and positive mood and energy dysregulation, accounting for clinical and demographic variables. Non-zero coefficients between change in the above symptom measures and change in activity over the inter-scan interval were identified in right amygdala and left ventrolateral prefrontal cortex. Differing patterns of neural activity change were associated with changes in each of the above symptoms over time. Specifically, from Scan1 to Scan2, worsening affective lability and depression severity were associated with increased right amygdala and left ventrolateral prefrontal cortical activity. Worsening anxiety and positive mood and energy dysregulation were associated with decreased right amygdala and increased left ventrolateral prefrontal cortical activity. Worsening mania was associated with increased right amygdala and decreased left ventrolateral prefrontal cortical activity. These changes in neural activity between scans accounted for 13.6% of the variance; that is 25% of the total explained variance (39.6%) in these measures. Distinct neural mechanisms underlie changes in different mood and anxiety symptoms overtime.
Sensory Entrainment Mechanisms in Auditory Perception: Neural Synchronization Cortico-Striatal Activation.

PubMed

Sameiro-Barbosa, Catia M; Geiser, Eveline

2016-01-01

The auditory system displays modulations in sensitivity that can align with the temporal structure of the acoustic environment. This sensory entrainment can facilitate sensory perception and is particularly relevant for audition. Systems neuroscience is slowly uncovering the neural mechanisms underlying the behaviorally observed sensory entrainment effects in the human sensory system. The present article summarizes the prominent behavioral effects of sensory entrainment and reviews our current understanding of the neural basis of sensory entrainment, such as synchronized neural oscillations, and potentially, neural activation in the cortico-striatal system.
Locking of correlated neural activity to ongoing oscillations

PubMed Central

Helias, Moritz

2017-01-01

Population-wide oscillations are ubiquitously observed in mesoscopic signals of cortical activity. In these network states a global oscillatory cycle modulates the propensity of neurons to fire. Synchronous activation of neurons has been hypothesized to be a separate channel of signal processing information in the brain. A salient question is therefore if and how oscillations interact with spike synchrony and in how far these channels can be considered separate. Experiments indeed showed that correlated spiking co-modulates with the static firing rate and is also tightly locked to the phase of beta-oscillations. While the dependence of correlations on the mean rate is well understood in feed-forward networks, it remains unclear why and by which mechanisms correlations tightly lock to an oscillatory cycle. We here demonstrate that such correlated activation of pairs of neurons is qualitatively explained by periodically-driven random networks. We identify the mechanisms by which covariances depend on a driving periodic stimulus. Mean-field theory combined with linear response theory yields closed-form expressions for the cyclostationary mean activities and pairwise zero-time-lag covariances of binary recurrent random networks. Two distinct mechanisms cause time-dependent covariances: the modulation of the susceptibility of single neurons (via the external input and network feedback) and the time-varying variances of single unit activities. For some parameters, the effectively inhibitory recurrent feedback leads to resonant covariances even if mean activities show non-resonant behavior. Our analytical results open the question of time-modulated synchronous activity to a quantitative analysis. PMID:28604771
Associative memory model with spontaneous neural activity

NASA Astrophysics Data System (ADS)

Kurikawa, Tomoki; Kaneko, Kunihiko

2012-05-01

We propose a novel associative memory model wherein the neural activity without an input (i.e., spontaneous activity) is modified by an input to generate a target response that is memorized for recall upon the same input. Suitable design of synaptic connections enables the model to memorize input/output (I/O) mappings equaling 70% of the total number of neurons, where the evoked activity distinguishes a target pattern from others. Spontaneous neural activity without an input shows chaotic dynamics but keeps some similarity with evoked activities, as reported in recent experimental studies.
Maladaptive social information processing in childhood predicts young men’s atypical amygdala reactivity to threat

PubMed Central

Choe, Daniel Ewon; Shaw, Daniel S.; Forbes, Erika E.

2014-01-01

Background Maladaptive social information processing, such as hostile attributional bias and aggressive response generation, is associated with childhood maladjustment. Although social information processing problems are correlated with heightened physiological responses to social threat, few studies have examined their associations with neural threat circuitry, specifically amygdala activation to social threat. Methods A cohort of 310 boys participated in an ongoing longitudinal study and completed questionnaires and laboratory tasks assessing their social and cognitive characteristics between 10- and 12-years-old. At age 20, 178 of these young men underwent functional magnetic resonance imaging and a social threat task. At age 22, adult criminal arrest records and self-reports of impulsiveness were obtained. Results Path models indicated that maladaptive social information processing at ages 10 and 11 predicted increased left amygdala reactivity to fear faces, an ambiguous threat, at age 20 while accounting for childhood antisocial behavior, empathy, IQ, and socioeconomic status. Exploratory analyses indicated that aggressive response generation—the tendency to respond to threat with reactive aggression—predicted left amygdala reactivity to fear faces and was concurrently associated with empathy, antisocial behavior, and hostile attributional bias, whereas hostile attributional bias correlated with IQ. Although unrelated to social information processing problems, bilateral amygdala reactivity to anger faces at age 20 was unexpectedly predicted by low IQ at age 11. Amygdala activation did not mediate associations between social information processing and number of criminal arrests, but both impulsiveness at age 22 and arrests were correlated with right amygdala reactivity to anger facial expressions at age 20. Conclusions Childhood social information processing and IQ predicted young men’s amygdala response to threat a decade later, which suggests that childhood social-cognitive characteristics are associated with the development of neural threat processing and adult adjustment. PMID:25142952
Neuroprotective effects of human mesenchymal stem cells on neural cultures exposed to 6-hydroxydopamine: implications for reparative therapy in Parkinson's disease.

PubMed

Cova, Lidia; Bossolasco, Patrizia; Armentero, Marie-Therese; Diana, Valentina; Zennaro, Eleonora; Mellone, Manuela; Calzarossa, Cinzia; Cerri, Silvia; Deliliers, Giorgio Lambertenghi; Polli, Elio; Blandini, Fabio; Silani, Vincenzo

2012-03-01

Stem cell (SC) transplantation represents a promising tool to treat neurodegenerative disorders, such as Parkinson's disease (PD), but positive therapeutic outcomes require elucidation of the biological mechanisms involved. Therefore, we investigated human Mesenchymal SCs (hMSCs) ability to protect murine differentiated Neural SCs (mdNSCs) against the cytotoxic effects of 6-hydroxydopamine (6-OHDA) in a co-culture model mimicking the in vivo neurovascular niche. The internalization of 6-OHDA mainly relies on its uptake by the dopamine active transporter (DAT), but its toxicity could also involve other pathways. We demonstrated that mdNSCs consistently expressed DAT along the differentiative process. Exposure to 6-OHDA did not affect hMSCs, but induced DAT-independent apoptosis in mdNSCs with generation of reactive oxygen species and caspases 3/7 activation. The potential neuroprotective action of hMSCs on mdNSCs exposed to 6-OHDA was tested in different co-culture conditions, in which hMSCs were added to mdNSCs prior to, simultaneously, or after 6-OHDA treatment. In the presence of the neurotoxin, the majority of mdNSCs acquired an apoptotic phenotype, while co-cultures with hMSCs significantly increased their survival (up to 70%) in all conditions. Multiplex human angiogenic array analysis on the conditioned media demonstrated that cytokine release by hMSCs was finely modulated. Moreover, sole growth factor addition yielded a similar neuroprotective effect on mdNSCs. In conclusion, our findings demonstrate that hMSCs protect mdNSCs against 6-OHDA neurotoxicity, and rescue cells from ongoing neurodegeneration likely through the release of multiple cytokines. Our findings provide novel insights for the development of therapeutic strategies designed to counteract the neurodegenerative processes of PD.
Neuronal hyperexcitability in the ventral posterior thalamus of neuropathic rats: modality selective effects of pregabalin

PubMed Central

Dickenson, Anthony H.

2016-01-01

Neuropathic pain represents a substantial clinical challenge; understanding the underlying neural mechanisms and back-translation of therapeutics could aid targeting of treatments more effectively. The ventral posterior thalamus (VP) is the major termination site for the spinothalamic tract and relays nociceptive activity to the somatosensory cortex; however, under neuropathic conditions, it is unclear how hyperexcitability of spinal neurons converges onto thalamic relays. This study aimed to identify neural substrates of hypersensitivity and the influence of pregabalin on central processing. In vivo electrophysiology was performed to record from VP wide dynamic range (WDR) and nociceptive-specific (NS) neurons in anesthetized spinal nerve-ligated (SNL), sham-operated, and naive rats. In neuropathic rats, WDR neurons had elevated evoked responses to low- and high-intensity punctate mechanical stimuli, dynamic brushing, and innocuous and noxious cooling, but less so to heat stimulation, of the receptive field. NS neurons in SNL rats also displayed increased responses to noxious punctate mechanical stimulation, dynamic brushing, noxious cooling, and noxious heat. Additionally, WDR, but not NS, neurons in SNL rats exhibited substantially higher rates of spontaneous firing, which may correlate with ongoing pain. The ratio of WDR-to-NS neurons was comparable between SNL and naive/sham groups, suggesting relatively few NS neurons gain sensitivity to low-intensity stimuli leading to a “WDR phenotype.” After neuropathy was induced, the proportion of cold-sensitive WDR and NS neurons increased, supporting the suggestion that changes in frequency-dependent firing and population coding underlie cold hypersensitivity. In SNL rats, pregabalin inhibited mechanical and heat responses but not cold-evoked or elevated spontaneous activity. PMID:27098028
Neuronal hyperexcitability in the ventral posterior thalamus of neuropathic rats: modality selective effects of pregabalin.

PubMed

Patel, Ryan; Dickenson, Anthony H

2016-07-01

Neuropathic pain represents a substantial clinical challenge; understanding the underlying neural mechanisms and back-translation of therapeutics could aid targeting of treatments more effectively. The ventral posterior thalamus (VP) is the major termination site for the spinothalamic tract and relays nociceptive activity to the somatosensory cortex; however, under neuropathic conditions, it is unclear how hyperexcitability of spinal neurons converges onto thalamic relays. This study aimed to identify neural substrates of hypersensitivity and the influence of pregabalin on central processing. In vivo electrophysiology was performed to record from VP wide dynamic range (WDR) and nociceptive-specific (NS) neurons in anesthetized spinal nerve-ligated (SNL), sham-operated, and naive rats. In neuropathic rats, WDR neurons had elevated evoked responses to low- and high-intensity punctate mechanical stimuli, dynamic brushing, and innocuous and noxious cooling, but less so to heat stimulation, of the receptive field. NS neurons in SNL rats also displayed increased responses to noxious punctate mechanical stimulation, dynamic brushing, noxious cooling, and noxious heat. Additionally, WDR, but not NS, neurons in SNL rats exhibited substantially higher rates of spontaneous firing, which may correlate with ongoing pain. The ratio of WDR-to-NS neurons was comparable between SNL and naive/sham groups, suggesting relatively few NS neurons gain sensitivity to low-intensity stimuli leading to a "WDR phenotype." After neuropathy was induced, the proportion of cold-sensitive WDR and NS neurons increased, supporting the suggestion that changes in frequency-dependent firing and population coding underlie cold hypersensitivity. In SNL rats, pregabalin inhibited mechanical and heat responses but not cold-evoked or elevated spontaneous activity. Copyright © 2016 the American Physiological Society.
[The mechanism and function of hippocampal neural oscillation].

PubMed

Lu, Ning; Xing, Dan-Qin; Sheng, Tao; Lu, Wei

2017-10-25

Neural oscillation is rhythmic or repetitive neural activity in the central nervous system that is usually generated by oscillatory activity of neuronal ensembles, reflecting regular and synchronized activities within these cell populations. According to several oscillatory bands covering frequencies from approximately 0.5 Hz to >100 Hz, neural oscillations are usually classified as delta oscillation (0.5-3 Hz), theta oscillation (4-12 Hz), beta oscillation (12-30 Hz), gamma oscillation (30-100 Hz) and sharp-wave ripples (>100 Hz ripples superimposed on 0.01-3 Hz sharp waves). Neural oscillation in different frequencies can be detected in different brain regions of human and animal during perception, motion and sleep, and plays an essential role in cognition, learning and memory process. In this review, we summarize recent findings on neural oscillations in hippocampus, as well as the mechanism and function of hippocampal theta oscillation, gamma oscillation and sharp-wave ripples. This review may yield new insights into the functions of neural oscillation in general.
High baseline activity in inferior temporal cortex improves neural and behavioral discriminability during visual categorization

PubMed Central

Emadi, Nazli; Rajimehr, Reza; Esteky, Hossein

2014-01-01

Spontaneous firing is a ubiquitous property of neural activity in the brain. Recent literature suggests that this baseline activity plays a key role in perception. However, it is not known how the baseline activity contributes to neural coding and behavior. Here, by recording from the single neurons in the inferior temporal cortex of monkeys performing a visual categorization task, we thoroughly explored the relationship between baseline activity, the evoked response, and behavior. Specifically we found that a low-frequency (<8 Hz) oscillation in the spike train, prior and phase-locked to the stimulus onset, was correlated with increased gamma power and neuronal baseline activity. This enhancement of the baseline activity was then followed by an increase in the neural selectivity and the response reliability and eventually a higher behavioral performance. PMID:25404900
Fast fMRI can detect oscillatory neural activity in humans.

PubMed

Lewis, Laura D; Setsompop, Kawin; Rosen, Bruce R; Polimeni, Jonathan R

2016-10-25

Oscillatory neural dynamics play an important role in the coordination of large-scale brain networks. High-level cognitive processes depend on dynamics evolving over hundreds of milliseconds, so measuring neural activity in this frequency range is important for cognitive neuroscience. However, current noninvasive neuroimaging methods are not able to precisely localize oscillatory neural activity above 0.2 Hz. Electroencephalography and magnetoencephalography have limited spatial resolution, whereas fMRI has limited temporal resolution because it measures vascular responses rather than directly recording neural activity. We hypothesized that the recent development of fast fMRI techniques, combined with the extra sensitivity afforded by ultra-high-field systems, could enable precise localization of neural oscillations. We tested whether fMRI can detect neural oscillations using human visual cortex as a model system. We detected small oscillatory fMRI signals in response to stimuli oscillating at up to 0.75 Hz within single scan sessions, and these responses were an order of magnitude larger than predicted by canonical linear models. Simultaneous EEG-fMRI and simulations based on a biophysical model of the hemodynamic response to neuronal activity suggested that the blood oxygen level-dependent response becomes faster for rapidly varying stimuli, enabling the detection of higher frequencies than expected. Accounting for phase delays across voxels further improved detection, demonstrating that identifying vascular delays will be of increasing importance with higher-frequency activity. These results challenge the assumption that the hemodynamic response is slow, and demonstrate that fMRI has the potential to map neural oscillations directly throughout the brain.
NeMO-Net & Fluid Lensing: The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment Using Fluid Lensing Augmentation of NASA EOS Data

NASA Technical Reports Server (NTRS)

Chirayath, Ved

2018-01-01

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low-resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.
Dynamic Neural State Identification in Deep Brain Local Field Potentials of Neuropathic Pain.

PubMed

Luo, Huichun; Huang, Yongzhi; Du, Xueying; Zhang, Yunpeng; Green, Alexander L; Aziz, Tipu Z; Wang, Shouyan

2018-01-01

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

PubMed Central

Luo, Huichun; Huang, Yongzhi; Du, Xueying; Zhang, Yunpeng; Green, Alexander L.; Aziz, Tipu Z.; Wang, Shouyan

2018-01-01

In neuropathic pain, the neurophysiological and neuropathological function of the ventro-posterolateral nucleus of the thalamus (VPL) and the periventricular gray/periaqueductal gray area (PVAG) involves multiple frequency oscillations. Moreover, oscillations related to pain perception and modulation change dynamically over time. Fluctuations in these neural oscillations reflect the dynamic neural states of the nucleus. In this study, an approach to classifying the synchronization level was developed to dynamically identify the neural states. An oscillation extraction model based on windowed wavelet packet transform was designed to characterize the activity level of oscillations. The wavelet packet coefficients sparsely represented the activity level of theta and alpha oscillations in local field potentials (LFPs). Then, a state discrimination model was designed to calculate an adaptive threshold to determine the activity level of oscillations. Finally, the neural state was represented by the activity levels of both theta and alpha oscillations. The relationship between neural states and pain relief was further evaluated. The performance of the state identification approach achieved sensitivity and specificity beyond 80% in simulation signals. Neural states of the PVAG and VPL were dynamically identified from LFPs of neuropathic pain patients. The occurrence of neural states based on theta and alpha oscillations were correlated to the degree of pain relief by deep brain stimulation. In the PVAG LFPs, the occurrence of the state with high activity levels of theta oscillations independent of alpha and the state with low-level alpha and high-level theta oscillations were significantly correlated with pain relief by deep brain stimulation. This study provides a reliable approach to identifying the dynamic neural states in LFPs with a low signal-to-noise ratio by using sparse representation based on wavelet packet transform. Furthermore, it may advance closed-loop deep brain stimulation based on neural states integrating multiple neural oscillations. PMID:29695951
A Role for the Lateral Dorsal Tegmentum in Memory and Decision Neural Circuitry

PubMed Central

Redila, Van; Kinzel, Chantelle; Jo, Yong Sang; Puryear, Corey B.; Mizumori, Sheri J.Y.

2017-01-01

A role for the hippocampus in memory is clear, although the mechanism for its contribution remains a matter of debate. Converging evidence suggests that hippocampus evaluates the extent to which context-defining features of events occur as expected. The consequence of mismatches, or prediction error, signals from hippocampus is discussed in terms of its impact on neural circuitry that evaluates the significance of prediction errors: Ventral tegmental area (VTA) dopamine cells burst fire to rewards or cues that predict rewards (Schultz et al., 1997). Although the lateral dorsal tegmentum (LDTg) importantly controls dopamine cell burst firing (Lodge & Grace, 2006) the behavioral significance of the LDTg control is not known. Therefore, we evaluated LDTg functional activity as rats performed a spatial memory task that generates task-dependent reward codes in VTA (Jo et al., 2013; Puryear et al., 2010) and another VTA afferent, the pedunculopontine nucleus (PPTg, Norton et al., 2011). Reversible inactivation of the LDTg significantly impaired choice accuracy. LDTg neurons coded primarily egocentric information in the form of movement velocity, turning behaviors, and behaviors leading up to expected reward locations. A subset of the velocity-tuned LDTg cells also showed high frequency bursts shortly before or after reward encounters, after which they showed tonic elevated firing during consumption of small, but not large, rewards. Cells that fired before reward encounters showed stronger correlations with velocity as rats moved toward, rather than away from, rewarded sites. LDTg neural activity was more strongly regulated by egocentric behaviors than that observed for PPTg or VTA cells that were recorded by Puryear et al. and Norton et al. While PPTg activity was uniquely sensitive to ongoing sensory input, all three regions encoded reward magnitude (although in different ways), reward expectation, and reward encounters. Only VTA encoded reward prediction errors. LDTg may inform VTA about learned goal-directed movement that reflects the current motivational state, and this in turn may guide VTA determination of expected subjective goal values. When combined it is clear the LDTg and PPTg provide only a portion of the information that dopamine cells need to assess the value of prediction errors, a process that is essential to future adaptive decisions and switches of cognitive (i.e. memorial) strategies and behavioral responses. PMID:24910282
Cognitive deficits caused by prefrontal cortical and hippocampal neural disinhibition.

PubMed

Bast, Tobias; Pezze, Marie; McGarrity, Stephanie

2017-10-01

We review recent evidence concerning the significance of inhibitory GABA transmission and of neural disinhibition, that is, deficient GABA transmission, within the prefrontal cortex and the hippocampus, for clinically relevant cognitive functions. Both regions support important cognitive functions, including attention and memory, and their dysfunction has been implicated in cognitive deficits characterizing neuropsychiatric disorders. GABAergic inhibition shapes cortico-hippocampal neural activity, and, recently, prefrontal and hippocampal neural disinhibition has emerged as a pathophysiological feature of major neuropsychiatric disorders, especially schizophrenia and age-related cognitive decline. Regional neural disinhibition, disrupting spatio-temporal control of neural activity and causing aberrant drive of projections, may disrupt processing within the disinhibited region and efferent regions. Recent studies in rats showed that prefrontal and hippocampal neural disinhibition (by local GABA antagonist microinfusion) dysregulates burst firing, which has been associated with important aspects of neural information processing. Using translational tests of clinically relevant cognitive functions, these studies showed that prefrontal and hippocampal neural disinhibition disrupts regional cognitive functions (including prefrontal attention and hippocampal memory function). Moreover, hippocampal neural disinhibition disrupted attentional performance, which does not require the hippocampus but requires prefrontal-striatal circuits modulated by the hippocampus. However, some prefrontal and hippocampal functions (including inhibitory response control) are spared by regional disinhibition. We consider conceptual implications of these findings, regarding the distinct relationships of distinct cognitive functions to prefrontal and hippocampal GABA tone and neural activity. Moreover, the findings support the proposition that prefrontal and hippocampal neural disinhibition contributes to clinically relevant cognitive deficits, and we consider pharmacological strategies for ameliorating cognitive deficits by rebalancing disinhibition-induced aberrant neural activity. Linked Articles This article is part of a themed section on Pharmacology of Cognition: a Panacea for Neuropsychiatric Disease? To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.19/issuetoc. © 2017 The British Pharmacological Society.

Trial-by-Trial Motor Cortical Correlates of a Rapidly Adapting Visuomotor Internal Model

PubMed Central

Ryu, Stephen I.

2017-01-01

Accurate motor control is mediated by internal models of how neural activity generates movement. We examined neural correlates of an adapting internal model of visuomotor gain in motor cortex while two macaques performed a reaching task in which the gain scaling between the hand and a presented cursor was varied. Previous studies of cortical changes during visuomotor adaptation focused on preparatory and perimovement epochs and analyzed trial-averaged neural data. Here, we recorded simultaneous neural population activity using multielectrode arrays and focused our analysis on neural differences in the period before the target appeared. We found that we could estimate the monkey's internal model of the gain using the neural population state during this pretarget epoch. This neural correlate depended on the gain experienced during recent trials and it predicted the speed of the subsequent reach. To explore the utility of this internal model estimate for brain–machine interfaces, we performed an offline analysis showing that it can be used to compensate for upcoming reach extent errors. Together, these results demonstrate that pretarget neural activity in motor cortex reflects the monkey's internal model of visuomotor gain on single trials and can potentially be used to improve neural prostheses. SIGNIFICANCE STATEMENT When generating movement commands, the brain is believed to use internal models of the relationship between neural activity and the body's movement. Visuomotor adaptation tasks have revealed neural correlates of these computations in multiple brain areas during movement preparation and execution. Here, we describe motor cortical changes in a visuomotor gain change task even before a specific movement is cued. We were able to estimate the gain internal model from these pretarget neural correlates and relate it to single-trial behavior. This is an important step toward understanding the sensorimotor system's algorithms for updating its internal models after specific movements and errors. Furthermore, the ability to estimate the internal model before movement could improve motor neural prostheses being developed for people with paralysis. PMID:28087767
Spinal TNFα is necessary for inactivity-induced phrenic motor facilitation

PubMed Central

Broytman, Oleg; Baertsch, Nathan A; Baker-Herman, Tracy L

2013-01-01

A prolonged reduction in central neural respiratory activity elicits a form of plasticity known as inactivity-induced phrenic motor facilitation (iPMF), a ‘rebound’ increase in phrenic burst amplitude apparent once respiratory neural activity is restored. iPMF requires atypical protein kinase C (aPKC) activity within spinal segments containing the phrenic motor nucleus to stabilize an early transient increase in phrenic burst amplitude and to form long-lasting iPMF following reduced respiratory neural activity. Upstream signal(s) leading to spinal aPKC activation are unknown. We tested the hypothesis that spinal tumour necrosis factor-α (TNFα) is necessary for iPMF via an aPKC-dependent mechanism. Anaesthetized, ventilated rats were exposed to a 30 min neural apnoea; upon resumption of respiratory neural activity, a prolonged increase in phrenic burst amplitude (42 ± 9% baseline; P < 0.05) was apparent, indicating long-lasting iPMF. Pretreatment with recombinant human soluble TNF receptor 1 (sTNFR1) in the intrathecal space at the level of the phrenic motor nucleus prior to neural apnoea blocked long-lasting iPMF (2 ± 8% baseline; P > 0.05). Intrathecal TNFα without neural apnoea was sufficient to elicit long-lasting phrenic motor facilitation (pMF; 62 ± 7% baseline; P < 0.05). Similar to iPMF, TNFα-induced pMF required spinal aPKC activity, as intrathecal delivery of a ζ-pseudosubstrate inhibitory peptide (PKCζ-PS) 35 min following intrathecal TNFα arrested TNFα-induced pMF (28 ± 8% baseline; P < 0.05). These data demonstrate that: (1) spinal TNFα is necessary for iPMF; and (2) spinal TNFα is sufficient to elicit pMF via a similar aPKC-dependent mechanism. These data are consistent with the hypothesis that reduced respiratory neural activity elicits iPMF via a TNFα-dependent increase in spinal aPKC activity. PMID:23878370
Object-processing neural efficiency differentiates object from spatial visualizers.

PubMed

Motes, Michael A; Malach, Rafael; Kozhevnikov, Maria

2008-11-19

The visual system processes object properties and spatial properties in distinct subsystems, and we hypothesized that this distinction might extend to individual differences in visual processing. We conducted a functional MRI study investigating the neural underpinnings of individual differences in object versus spatial visual processing. Nine participants of high object-processing ability ('object' visualizers) and eight participants of high spatial-processing ability ('spatial' visualizers) were scanned, while they performed an object-processing task. Object visualizers showed lower bilateral neural activity in lateral occipital complex and lower right-lateralized neural activity in dorsolateral prefrontal cortex. The data indicate that high object-processing ability is associated with more efficient use of visual-object resources, resulting in less neural activity in the object-processing pathway.
Neural plasticity and its initiating conditions in tinnitus.

PubMed

Roberts, L E

2018-03-01

Deafferentation caused by cochlear pathology (which can be hidden from the audiogram) activates forms of neural plasticity in auditory pathways, generating tinnitus and its associated conditions including hyperacusis. This article discusses tinnitus mechanisms and suggests how these mechanisms may relate to those involved in normal auditory information processing. Research findings from animal models of tinnitus and from electromagnetic imaging of tinnitus patients are reviewed which pertain to the role of deafferentation and neural plasticity in tinnitus and hyperacusis. Auditory neurons compensate for deafferentation by increasing their input/output functions (gain) at multiple levels of the auditory system. Forms of homeostatic plasticity are believed to be responsible for this neural change, which increases the spontaneous and driven activity of neurons in central auditory structures in animals expressing behavioral evidence of tinnitus. Another tinnitus correlate, increased neural synchrony among the affected neurons, is forged by spike-timing-dependent neural plasticity in auditory pathways. Slow oscillations generated by bursting thalamic neurons verified in tinnitus animals appear to modulate neural plasticity in the cortex, integrating tinnitus neural activity with information in brain regions supporting memory, emotion, and consciousness which exhibit increased metabolic activity in tinnitus patients. The latter process may be induced by transient auditory events in normal processing but it persists in tinnitus, driven by phantom signals from the auditory pathway. Several tinnitus therapies attempt to suppress tinnitus through plasticity, but repeated sessions will likely be needed to prevent tinnitus activity from returning owing to deafferentation as its initiating condition.
Greater neural pattern similarity across repetitions is associated with better memory.

PubMed

Xue, Gui; Dong, Qi; Chen, Chuansheng; Lu, Zhonglin; Mumford, Jeanette A; Poldrack, Russell A

2010-10-01

Repeated study improves memory, but the underlying neural mechanisms of this improvement are not well understood. Using functional magnetic resonance imaging and representational similarity analysis of brain activity, we found that, compared with forgotten items, subsequently remembered faces and words showed greater similarity in neural activation across multiple study in many brain regions, including (but not limited to) the regions whose mean activities were correlated with subsequent memory. This result addresses a longstanding debate in the study of memory by showing that successful episodic memory encoding occurs when the same neural representations are more precisely reactivated across study episodes, rather than when patterns of activation are more variable across time.
Self-Affirmation Activates the Ventral Striatum: A Possible Reward-Related Mechanism for Self-Affirmation.

PubMed

Dutcher, Janine M; Creswell, J David; Pacilio, Laura E; Harris, Peter R; Klein, William M P; Levine, John M; Bower, Julienne E; Muscatell, Keely A; Eisenberger, Naomi I

2016-04-01

Self-affirmation (reflecting on important personal values) has been shown to have a range of positive effects; however, the neural basis of self-affirmation is not known. Building on studies showing that thinking about self-preferences activates neural reward pathways, we hypothesized that self-affirmation would activate brain reward circuitry during functional MRI (fMRI) studies. In Study 1, with college students, making judgments about important personal values during self-affirmation activated neural reward regions (i.e., ventral striatum), whereas making preference judgments that were not self-relevant did not. Study 2 replicated these results in a community sample, again showing that self-affirmation activated the ventral striatum. These are among the first fMRI studies to identify neural processes during self-affirmation. The findings extend theory by showing that self-affirmation may be rewarding and may provide a first step toward identifying a neural mechanism by which self-affirmation may produce a wide range of beneficial effects. © The Author(s) 2016.
Multistability of memristive Cohen-Grossberg neural networks with non-monotonic piecewise linear activation functions and time-varying delays.

PubMed

Nie, Xiaobing; Zheng, Wei Xing; Cao, Jinde

2015-11-01

The problem of coexistence and dynamical behaviors of multiple equilibrium points is addressed for a class of memristive Cohen-Grossberg neural networks with non-monotonic piecewise linear activation functions and time-varying delays. By virtue of the fixed point theorem, nonsmooth analysis theory and other analytical tools, some sufficient conditions are established to guarantee that such n-dimensional memristive Cohen-Grossberg neural networks can have 5(n) equilibrium points, among which 3(n) equilibrium points are locally exponentially stable. It is shown that greater storage capacity can be achieved by neural networks with the non-monotonic activation functions introduced herein than the ones with Mexican-hat-type activation function. In addition, unlike most existing multistability results of neural networks with monotonic activation functions, those obtained 3(n) locally stable equilibrium points are located both in saturated regions and unsaturated regions. The theoretical findings are verified by an illustrative example with computer simulations. Copyright © 2015 Elsevier Ltd. All rights reserved.
Frequency characteristics of human muscle and cortical responses evoked by noisy Achilles tendon vibration.

PubMed

Mildren, Robyn L; Peters, Ryan M; Hill, Aimee J; Blouin, Jean-Sébastien; Carpenter, Mark G; Inglis, J Timothy

2017-05-01

Noisy stimuli, along with linear systems analysis, have proven to be effective for mapping functional neural connections. We explored the use of noisy (10-115 Hz) Achilles tendon vibration to examine somatosensory reflexes in the triceps surae muscles in standing healthy young adults ( n = 8). We also examined the association between noisy vibration and electrical activity recorded over the sensorimotor cortex using electroencephalography. We applied 2 min of vibration and recorded ongoing muscle activity of the soleus and gastrocnemii using surface electromyography (EMG). Vibration amplitude was varied to characterize reflex scaling and to examine how different stimulus levels affected postural sway. Muscle activity from the soleus and gastrocnemii was significantly correlated with the tendon vibration across a broad frequency range (~10-80 Hz), with a peak located at ~40 Hz. Vibration-EMG coherence positively scaled with stimulus amplitude in all three muscles, with soleus displaying the strongest coupling and steepest scaling. EMG responses lagged the vibration by ~38 ms, a delay that paralleled observed response latencies to tendon taps. Vibration-evoked cortical oscillations were observed at frequencies ~40-70 Hz (peak ~54 Hz) in most subjects, a finding in line with previous reports of sensory-evoked γ-band oscillations. Further examination of the method revealed 1 ) accurate reflex estimates could be obtained with <60 s of low-level (root mean square = 10 m/s 2 ) vibration; 2 ) responses did not habituate over 2 min of exposure; and importantly, 3 ) noisy vibration had a minimal influence on standing balance. Our findings suggest noisy tendon vibration is an effective novel approach to characterize somatosensory reflexes during standing. NEW & NOTEWORTHY We applied noisy (10-115 Hz) vibration to the Achilles tendon to examine the frequency characteristics of lower limb somatosensory reflexes during standing. Ongoing muscle activity was coherent with the noisy vibration (peak coherence ~40 Hz), and coherence positively scaled with increases in stimulus amplitude. Our findings suggest that noisy tendon vibration, along with linear systems analysis, is an effective novel approach to study somatosensory reflex actions in active muscles. Copyright © 2017 the American Physiological Society.
Decoding-Accuracy-Based Sequential Dimensionality Reduction of Spatio-Temporal Neural Activities

NASA Astrophysics Data System (ADS)

Funamizu, Akihiro; Kanzaki, Ryohei; Takahashi, Hirokazu

Performance of a brain machine interface (BMI) critically depends on selection of input data because information embedded in the neural activities is highly redundant. In addition, properly selected input data with a reduced dimension leads to improvement of decoding generalization ability and decrease of computational efforts, both of which are significant advantages for the clinical applications. In the present paper, we propose an algorithm of sequential dimensionality reduction (SDR) that effectively extracts motor/sensory related spatio-temporal neural activities. The algorithm gradually reduces input data dimension by dropping neural data spatio-temporally so as not to undermine the decoding accuracy as far as possible. Support vector machine (SVM) was used as the decoder, and tone-induced neural activities in rat auditory cortices were decoded into the test tone frequencies. SDR reduced the input data dimension to a quarter and significantly improved the accuracy of decoding of novel data. Moreover, spatio-temporal neural activity patterns selected by SDR resulted in significantly higher accuracy than high spike rate patterns or conventionally used spatial patterns. These results suggest that the proposed algorithm can improve the generalization ability and decrease the computational effort of decoding.
Virtual Reality as an Adjunctive Non-pharmacologic Analgesic for Acute Burn Pain During Medical Procedures

PubMed Central

Chambers, Gloria T.; Meyer, Walter J.; Arceneaux, Lisa L.; Russell, William J.; Seibel, Eric J.; Richards, Todd L.; Sharar, Sam R.; Patterson, David R.

2015-01-01

Introduction Excessive pain during medical procedures is a widespread problem but is especially problematic during daily wound care of patients with severe burn injuries. Methods Burn patients report 35–50% reductions in procedural pain while in a distracting immersive virtual reality, and fMRI brain scans show associated reductions in pain-related brain activity during VR. VR distraction appears to be most effective for patients with the highest pain intensity levels. VR is thought to reduce pain by directing patients’ attention into the virtual world, leaving less attention available to process incoming neural signals from pain receptors. Conclusions We review evidence from clinical and laboratory research studies exploring Virtual Reality analgesia, concentrating primarily on the work ongoing within our group. We briefly describe how VR pain distraction systems have been tailored to the unique needs of burn patients to date, and speculate about how VR systems could be tailored to the needs of other patient populations in the future. PMID:21264690
Brain oscillations track the formation of episodic memories in the real world.

PubMed

Griffiths, Benjamin; Mazaheri, Ali; Debener, Stefan; Hanslmayr, Simon

2016-12-01

Despite the well-known influence of environmental context on episodic memory, little has been done to increase contextual richness within the lab. This leaves a blind spot lingering over the neuronal correlates of episodic memory formation in day-to-day life. To address this, we presented participants with a series of words to memorise along a pre-designated route across campus while a mobile EEG system acquired ongoing neural activity. Replicating lab-based subsequent memory effects (SMEs), we identified significant low to mid frequency power decreases (<30Hz), including beta power decreases over the left inferior frontal gyrus. When investigating the oscillatory correlates of temporal and spatial context binding, we found that items strongly bound to spatial context exhibited significantly greater theta power decreases than items strongly bound to temporal context. These findings expand upon lab-based studies by demonstrating the influence of real world contextual factors that underpin memory formation. Copyright Â© 2016 Elsevier Inc. All rights reserved.
Neural activity during interoceptive awareness and its associations with alexithymia—An fMRI study in major depressive disorder and non-psychiatric controls

PubMed Central

Wiebking, Christine; Northoff, Georg

2015-01-01

Objective: Alexithymia relates to difficulties recognizing and describing emotions. It has been linked to subjectively increased interoceptive awareness (IA) and to psychiatric illnesses such as major depressive disorder (MDD) and somatization. MDD in turn is characterized by aberrant emotion processing and IA on the subjective as well as on the neural level. However, a link between neural activity in response to IA and alexithymic traits in health and depression remains unclear. Methods: A well-established fMRI task was used to investigate neural activity during IA (heartbeat counting) and exteroceptive awareness (tone counting) in non-psychiatric controls (NC) and MDD. Firstly, comparing MDD and NC, a linear relationship between IA-related activity and scores of the Toronto Alexithymia Scale (TAS) was investigated through whole-brain regression. Secondly, NC were divided by median-split of TAS scores into groups showing low (NC-low) or high (NC-high) alexithymia. MDD and NC-high showed equally high TAS scores. Subsequently, IA-related neural activity was compared on a whole-brain level between the three independent samples (MDD, NC-low, NC-high). Results: Whole-brain regressions between MDD and NC revealed neural differences during IA as a function of TAS-DD (subscale difficulty describing feelings) in the supragenual anterior cingulate cortex (sACC; BA 24/32), which were due to negative associations between TAS-DD and IA-related activity in NC. Contrasting NC subgroups after median-split on a whole-brain level, high TAS scores were associated with decreased neural activity during IA in the sACC and increased insula activity. Though having equally high alexithymia scores, NC-high showed increased insula activity during IA compared to MDD, whilst both groups showed decreased activity in the sACC. Conclusions: Within the context of decreased sACC activity during IA in alexithymia (NC-high and MDD), increased insula activity might mirror a compensatory mechanism in NC-high, which is disrupted in MDD. PMID:26074827
Monitoring Neural Activity with Bioluminescence during Natural Behavior

PubMed Central

Naumann, Eva A.; Kampff, Adam R.; Prober, David A.; Schier, Alexander F.; Engert, Florian

2010-01-01

Existing techniques for monitoring neural activity in awake, freely behaving vertebrates are invasive and difficult to target to genetically identified neurons. Here we describe the use of bioluminescence to non-invasively monitor the activity of genetically specified neurons in freely behaving zebrafish. Transgenic fish expressing the Ca2+-sensitive photoprotein GFP-apoAequorin (GA) in most neurons generated large and fast bioluminescent signals related to neural activity, neuroluminescence, that could be recorded continuously for many days. To test the limits of this technique, GA was specifically targeted to the hypocretin-positive neurons of the hypothalamus. We found that neuroluminescence generated by this group of ~20 neurons was associated with periods of increased locomotor activity and identified two classes of neural activity corresponding to distinct swim latencies. Thus, our neuroluminescence assay can report, with high temporal resolution and sensitivity, the activity of small subsets of neurons during unrestrained behavior. PMID:20305645
Neural activity to intense positive versus negative stimuli can help differentiate bipolar disorder from unipolar major depressive disorder in depressed adolescents: a pilot fMRI study.

PubMed

Diler, Rasim Somer; de Almeida, Jorge Renner Cardoso; Ladouceur, Cecile; Birmaher, Boris; Axelson, David; Phillips, Mary

2013-12-30

Failure to distinguish bipolar depression (BDd) from the unipolar depression of major depressive disorder (UDd) in adolescents has significant clinical consequences. We aimed to identify differential patterns of functional neural activity in BDd versus UDd and employed two (fearful and happy) facial expression/ gender labeling functional magnetic resonance imaging (fMRI) experiments to study emotion processing in 10 BDd (8 females, mean age=15.1 ± 1.1) compared to age- and gender-matched 10 UDd and 10 healthy control (HC) adolescents who were age- and gender-matched to the BDd group. BDd adolescents, relative to UDd, showed significantly lower activity to both intense happy (e.g., insula and temporal cortex) and intense fearful faces (e.g., frontal precentral cortex). Although the neural regions recruited in each group were not the same, both BDd and UDd adolescents, relative to HC, showed significantly lower neural activity to intense happy and mild happy faces, but elevated neural activity to mild fearful faces. Our results indicated that patterns of neural activity to intense positive and negative emotional stimuli can help differentiate BDd from UDd in adolescents. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Time Series Analysis of Soil Radon Data Using Multiple Linear Regression and Artificial Neural Network in Seismic Precursory Studies

NASA Astrophysics Data System (ADS)

Singh, S.; Jaishi, H. P.; Tiwari, R. P.; Tiwari, R. C.

2017-07-01

This paper reports the analysis of soil radon data recorded in the seismic zone-V, located in the northeastern part of India (latitude 23.73N, longitude 92.73E). Continuous measurements of soil-gas emission along Chite fault in Mizoram (India) were carried out with the replacement of solid-state nuclear track detectors at weekly interval. The present study was done for the period from March 2013 to May 2015 using LR-115 Type II detectors, manufactured by Kodak Pathe, France. In order to reduce the influence of meteorological parameters, statistical analysis tools such as multiple linear regression and artificial neural network have been used. Decrease in radon concentration was recorded prior to some earthquakes that occurred during the observation period. Some false anomalies were also recorded which may be attributed to the ongoing crustal deformation which was not major enough to produce an earthquake.
SPIDER OR NO SPIDER? NEURAL CORRELATES OF SUSTAINED AND PHASIC FEAR IN SPIDER PHOBIA.

PubMed

Münsterkötter, Anna Luisa; Notzon, Swantje; Redlich, Ronny; Grotegerd, Dominik; Dohm, Katharina; Arolt, Volker; Kugel, Harald; Zwanzger, Peter; Dannlowski, Udo

2015-09-01

Processes of phasic fear responses to threatening stimuli are thought to be distinct from sustained, anticipatory anxiety toward an unpredicted, potential threat. There is evidence for dissociable neural correlates of phasic fear and sustained anxiety. Whereas increased amygdala activity has been associated with phasic fear, sustained anxiety has been linked with activation of the bed nucleus of stria terminalis (BNST), anterior cingulate cortex (ACC), and the insula. So far, only a few studies have focused on the dissociation of neural processes related to both phasic and sustained fear in specific phobia. We suggested that first, conditions of phasic and sustained fear would involve different neural networks and, second, that overall neural activity would be enhanced in a sample of phobic compared to nonphobic participants. Pictures of spiders and neutral stimuli under conditions of either predicted (phasic) or unpredicted (sustained) fear were presented to 28 subjects with spider phobia and 28 nonphobic control subjects during functional magnetic resonance imaging (fMRI) scanning. Phobic patients revealed significantly higher amygdala activation than controls under conditions of phasic fear. Sustained fear processing was significantly related to activation in the insula and ACC, and phobic patients showed a stronger activation than controls of the BNST and the right ACC under conditions of sustained fear. Functional connectivity analysis revealed enhanced connectivity of the BNST and the amygdala in phobic subjects. Our findings support the idea of distinct neural correlates of phasic and sustained fear processes. Increased neural activity and functional connectivity in these networks might be crucial for the development and maintenance of anxiety disorders. © 2015 Wiley Periodicals, Inc.
Hierarchically organized behavior and its neural foundations: A reinforcement-learning perspective

PubMed Central

Botvinick, Matthew M.; Niv, Yael; Barto, Andrew C.

2009-01-01

Research on human and animal behavior has long emphasized its hierarchical structure — the divisibility of ongoing behavior into discrete tasks, which are comprised of subtask sequences, which in turn are built of simple actions. The hierarchical structure of behavior has also been of enduring interest within neuroscience, where it has been widely considered to reflect prefrontal cortical functions. In this paper, we reexamine behavioral hierarchy and its neural substrates from the point of view of recent developments in computational reinforcement learning. Specifically, we consider a set of approaches known collectively as hierarchical reinforcement learning, which extend the reinforcement learning paradigm by allowing the learning agent to aggregate actions into reusable subroutines or skills. A close look at the components of hierarchical reinforcement learning suggests how they might map onto neural structures, in particular regions within the dorsolateral and orbital prefrontal cortex. It also suggests specific ways in which hierarchical reinforcement learning might provide a complement to existing psychological models of hierarchically structured behavior. A particularly important question that hierarchical reinforcement learning brings to the fore is that of how learning identifies new action routines that are likely to provide useful building blocks in solving a wide range of future problems. Here and at many other points, hierarchical reinforcement learning offers an appealing framework for investigating the computational and neural underpinnings of hierarchically structured behavior. PMID:18926527
Girls' challenging social experiences in early adolescence predict neural response to rewards and depressive symptoms.

PubMed

Casement, Melynda D; Guyer, Amanda E; Hipwell, Alison E; McAloon, Rose L; Hoffmann, Amy M; Keenan, Kathryn E; Forbes, Erika E

2014-04-01

Developmental models of psychopathology posit that exposure to social stressors may confer risk for depression in adolescent girls by disrupting neural reward circuitry. The current study tested this hypothesis by examining the relationship between early adolescent social stressors and later neural reward processing and depressive symptoms. Participants were 120 girls from an ongoing longitudinal study of precursors to depression across adolescent development. Low parental warmth, peer victimization, and depressive symptoms were assessed when the girls were 11 and 12 years old, and participants completed a monetary reward guessing fMRI task and assessment of depressive symptoms at age 16. Results indicate that low parental warmth was associated with increased response to potential rewards in the medial prefrontal cortex (mPFC), striatum, and amygdala, whereas peer victimization was associated with decreased response to potential rewards in the mPFC. Furthermore, concurrent depressive symptoms were associated with increased reward anticipation response in mPFC and striatal regions that were also associated with early adolescent psychosocial stressors, with mPFC and striatal response mediating the association between social stressors and depressive symptoms. These findings are consistent with developmental models that emphasize the adverse impact of early psychosocial stressors on neural reward processing and risk for depression in adolescence. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.
Spaceflight Effects on Neurocognitive Performance: Extent, Longevity and Neural Bases

NASA Technical Reports Server (NTRS)

Seidler, R. D.; Mulavara, A. P.; Koppelmans, V.; Kofman, I. S.; Cassady, K.; Yuan, P.; De Dios, Y. E.; Gadd, N.; Riascos, R. F.; Wood, S. J.;

2017-01-01

We are conducting ongoing experiments in which we are performing structural and functional magnetic resonance brain imaging to identify the relationships between changes in neurocognitive function and neural structural alterations following a six month International Space Station mission. Our central hypothesis is that measures of brain structure, function, and network integrity will change from pre to post spaceflight. Moreover, we predict that these changes will correlate with indices of cognitive, sensory, and motor function in a neuroanatomically selective fashion. Our interdisciplinary approach utilizes cutting edge neuroimaging techniques and a broad ranging battery of sensory, motor, and cognitive assessments that are conducted pre flight, during flight, and post flight to investigate potential neuroplastic and maladaptive brain changes in crewmembers following long-duration spaceflight. Success in this endeavor would 1) result in identification of the underlying neural mechanisms and operational risks of spaceflight-induced changes in behavior, and 2) identify whether a return to normative behavioral function following re-adaptation to Earth's gravitational environment is associated with a restitution of brain structure and function or instead is supported by substitution with compensatory brain processes. We have collected data on several crewmembers and preliminary findings will be presented. Eventual comparison to results from our parallel bed rest study will enable us to parse out the multiple mechanisms contributing to any spaceflight-induced neural structural and behavioral changes that we observe.

Experience-dependent emergence of beta and gamma band oscillations in the primary visual cortex during the critical period

PubMed Central

Chen, Guang; Rasch, Malte J.; Wang, Ran; Zhang, Xiao-hui

2015-01-01

Neural oscillatory activities have been shown to play important roles in neural information processing and the shaping of circuit connections during development. However, it remains unknown whether and how specific neural oscillations emerge during a postnatal critical period (CP), in which neuronal connections are most substantially modified by neural activity and experience. By recording local field potentials (LFPs) and single unit activity in developing primary visual cortex (V1) of head-fixed awake mice, we here demonstrate an emergence of characteristic oscillatory activities during the CP. From the pre-CP to CP, the peak frequency of spontaneous fast oscillatory activities shifts from the beta band (15–35 Hz) to the gamma band (40–70 Hz), accompanied by a decrease of cross-frequency coupling (CFC) and broadband spike-field coherence (SFC). Moreover, visual stimulation induced a large increase of beta-band activity but a reduction of gamma-band activity specifically from the CP onwards. Dark rearing of animals from the birth delayed this emergence of oscillatory activities during the CP, suggesting its dependence on early visual experience. These findings suggest that the characteristic neuronal oscillatory activities emerged specifically during the CP may represent as neural activity trait markers for the experience-dependent maturation of developing visual cortical circuits. PMID:26648548

The role of prestimulus activity in visual extinction☆

PubMed Central

Urner, Maren; Sarri, Margarita; Grahn, Jessica; Manly, Tom; Rees, Geraint; Friston, Karl

2013-01-01

Patients with visual extinction following right-hemisphere damage sometimes see and sometimes miss stimuli in the left visual field, particularly when stimuli are presented simultaneously to both visual fields. Awareness of left visual field stimuli is associated with increased activity in bilateral parietal and frontal cortex. However, it is unknown why patients see or miss these stimuli. Previous neuroimaging studies in healthy adults show that prestimulus activity biases perceptual decisions, and biases in visual perception can be attributed to fluctuations in prestimulus activity in task relevant brain regions. Here, we used functional MRI to investigate whether prestimulus activity affected perception in the context of visual extinction following stroke. We measured prestimulus activity in stimulus-responsive cortical areas during an extinction paradigm in a patient with unilateral right parietal damage and visual extinction. This allowed us to compare prestimulus activity on physically identical bilateral trials that either did or did not lead to visual extinction. We found significantly increased activity prior to stimulus presentation in two areas that were also activated by visual stimulation: the left calcarine sulcus and right occipital inferior cortex. Using dynamic causal modelling (DCM) we found that both these differences in prestimulus activity and stimulus evoked responses could be explained by enhanced effective connectivity within and between visual areas, prior to stimulus presentation. Thus, we provide evidence for the idea that differences in ongoing neural activity in visually responsive areas prior to stimulus onset affect awareness in visual extinction, and that these differences are mediated by fluctuations in extrinsic and intrinsic connectivity. PMID:23680398
The role of prestimulus activity in visual extinction.

PubMed

Urner, Maren; Sarri, Margarita; Grahn, Jessica; Manly, Tom; Rees, Geraint; Friston, Karl

2013-07-01

Patients with visual extinction following right-hemisphere damage sometimes see and sometimes miss stimuli in the left visual field, particularly when stimuli are presented simultaneously to both visual fields. Awareness of left visual field stimuli is associated with increased activity in bilateral parietal and frontal cortex. However, it is unknown why patients see or miss these stimuli. Previous neuroimaging studies in healthy adults show that prestimulus activity biases perceptual decisions, and biases in visual perception can be attributed to fluctuations in prestimulus activity in task relevant brain regions. Here, we used functional MRI to investigate whether prestimulus activity affected perception in the context of visual extinction following stroke. We measured prestimulus activity in stimulus-responsive cortical areas during an extinction paradigm in a patient with unilateral right parietal damage and visual extinction. This allowed us to compare prestimulus activity on physically identical bilateral trials that either did or did not lead to visual extinction. We found significantly increased activity prior to stimulus presentation in two areas that were also activated by visual stimulation: the left calcarine sulcus and right occipital inferior cortex. Using dynamic causal modelling (DCM) we found that both these differences in prestimulus activity and stimulus evoked responses could be explained by enhanced effective connectivity within and between visual areas, prior to stimulus presentation. Thus, we provide evidence for the idea that differences in ongoing neural activity in visually responsive areas prior to stimulus onset affect awareness in visual extinction, and that these differences are mediated by fluctuations in extrinsic and intrinsic connectivity. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.
Neural Energy Supply-Consumption Properties Based on Hodgkin-Huxley Model

PubMed Central

2017-01-01

Electrical activity is the foundation of the neural system. Coding theories that describe neural electrical activity by the roles of action potential timing or frequency have been thoroughly studied. However, an alternative method to study coding questions is the energy method, which is more global and economical. In this study, we clearly defined and calculated neural energy supply and consumption based on the Hodgkin-Huxley model, during firing action potentials and subthreshold activities using ion-counting and power-integral model. Furthermore, we analyzed energy properties of each ion channel and found that, under the two circumstances, power synchronization of ion channels and energy utilization ratio have significant differences. This is particularly true of the energy utilization ratio, which can rise to above 100% during subthreshold activity, revealing an overdraft property of energy use. These findings demonstrate the distinct status of the energy properties during neuronal firings and subthreshold activities. Meanwhile, after introducing a synapse energy model, this research can be generalized to energy calculation of a neural network. This is potentially important for understanding the relationship between dynamical network activities and cognitive behaviors. PMID:28316842
Combinatorial Fgf and Bmp signalling patterns the gastrula ectoderm into prospective neural and epidermal domains

PubMed Central

Kudoh, Tetsuhiro; Concha, Miguel L.; Houart, Corinne; Dawid, Igor B.; Wilson, Stephen W.

2009-01-01

Summary Studies in fish and amphibia have shown that graded Bmp signalling activity regulates dorsal-to-ventral (DV) patterning of the gastrula embryo. In the ectoderm, it is thought that high levels of Bmp activity promote epidermal development ventrally, whereas secreted Bmp antagonists emanating from the organiser induce neural tissue dorsally. However, in zebrafish embryos, the domain of cells destined to contribute to the spinal cord extends all the way to the ventral side of the gastrula, a long way from the organiser. We show that in vegetal (trunk and tail) regions of the zebrafish gastrula, neural specification is initiated at all DV positions of the ectoderm in a manner that is unaffected by levels of Bmp activity and independent of organiser-derived signals. Instead, we find that Fgf activity is required to induce vegetal prospective neural markers and can do so without suppressing Bmp activity. We further show that Bmp signalling does occur within the vegetal prospective neural domain and that Bmp activity promotes the adoption of caudal fate by this tissue. PMID:15262889
Isolating Discriminant Neural Activity in the Presence of Eye Movements and Concurrent Task Demands

PubMed Central

Touryan, Jon; Lawhern, Vernon J.; Connolly, Patrick M.; Bigdely-Shamlo, Nima; Ries, Anthony J.

2017-01-01

A growing number of studies use the combination of eye-tracking and electroencephalographic (EEG) measures to explore the neural processes that underlie visual perception. In these studies, fixation-related potentials (FRPs) are commonly used to quantify early and late stages of visual processing that follow the onset of each fixation. However, FRPs reflect a mixture of bottom-up (sensory-driven) and top-down (goal-directed) processes, in addition to eye movement artifacts and unrelated neural activity. At present there is little consensus on how to separate this evoked response into its constituent elements. In this study we sought to isolate the neural sources of target detection in the presence of eye movements and over a range of concurrent task demands. Here, participants were asked to identify visual targets (Ts) amongst a grid of distractor stimuli (Ls), while simultaneously performing an auditory N-back task. To identify the discriminant activity, we used independent components analysis (ICA) for the separation of EEG into neural and non-neural sources. We then further separated the neural sources, using a modified measure-projection approach, into six regions of interest (ROIs): occipital, fusiform, temporal, parietal, cingulate, and frontal cortices. Using activity from these ROIs, we identified target from non-target fixations in all participants at a level similar to other state-of-the-art classification techniques. Importantly, we isolated the time course and spectral features of this discriminant activity in each ROI. In addition, we were able to quantify the effect of cognitive load on both fixation-locked potential and classification performance across regions. Together, our results show the utility of a measure-projection approach for separating task-relevant neural activity into meaningful ROIs within more complex contexts that include eye movements. PMID:28736519
Neural Activations of Guided Imagery and Music in Negative Emotional Processing: A Functional MRI Study.

PubMed

Lee, Sang Eun; Han, Yeji; Park, HyunWook

2016-01-01

The Bonny Method of Guided Imagery and Music uses music and imagery to access and explore personal emotions associated with episodic memories. Understanding the neural mechanism of guided imagery and music (GIM) as combined stimuli for emotional processing informs clinical application. We performed functional magnetic resonance imaging (fMRI) to demonstrate neural mechanisms of GIM for negative emotional processing when personal episodic memory is recalled and re-experienced through GIM processes. Twenty-four healthy volunteers participated in the study, which used classical music and verbal instruction stimuli to evoke negative emotions. To analyze the neural mechanism, activated regions associated with negative emotional and episodic memory processing were extracted by conducting volume analyses for the contrast between GIM and guided imagery (GI) or music (M). The GIM stimuli showed increased activation over the M-only stimuli in five neural regions associated with negative emotional and episodic memory processing, including the left amygdala, left anterior cingulate gyrus, left insula, bilateral culmen, and left angular gyrus (AG). Compared with GI alone, GIM showed increased activation in three regions associated with episodic memory processing in the emotional context, including the right posterior cingulate gyrus, bilateral parahippocampal gyrus, and AG. No neural regions related to negative emotional and episodic memory processing showed more activation for M and GI than for GIM. As a combined multimodal stimulus, GIM may increase neural activations related to negative emotions and episodic memory processing. Findings suggest a neural basis for GIM with personal episodic memories affecting cortical and subcortical structures and functions. © the American Music Therapy Association 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Neural activation patterns during response inhibition distinguish adolescents with ADHD, their unaffected siblings, and healthy controls

PubMed Central

van Rooij, Daan; Hoekstra, Pieter J.; Mennes, Maarten; von Rhein, Daniel; Thissen, Andrieke J.A.M.; Heslenfeld, Dirk; Zwiers, Marcel P.; Faraone, Stephen V.; Oosterlaan, Jaap; Franke, Barbara; Rommelse, Nanda; Buitelaar, Jan K.; Hartman, Catharina A.

2015-01-01

Objective Impaired response inhibition is a key executive function deficit of attention-deficit/hyperactivity disorder (ADHD). Still, behavioral response inhibition measures do not consistently differentiate individuals with ADHD from unaffected individuals. We therefore investigated the neural correlates of response inhibition as well as the familial nature of these neural correlates. Methods fMRI measurements of neural activation during the stop-signal task along with behavioral measures of response inhibition were obtained in adolescents and young adults with ADHD (N=185), their unaffected siblings (N=111), and healthy controls (N=124). Results Stop-signal reaction times were longer in participants with ADHD, but not in their unaffected siblings, while reaction time variability and error rates were higher in both groups than in controls. Neural hypoactivation was observed in frontal-striatal and frontal-parietal networks of participants with ADHD and unaffected siblings compared to controls, whereby activation in inferior frontal and temporal/parietal nodes in unaffected siblings was intermediate between that of participants with ADHD and controls. Furthermore, neural activation in inferior frontal nodes correlated with stop-signal reaction times, and activation in both inferior frontal and temporal/parietal nodes correlated with ADHD severity. Conclusions Neural activation alterations in ADHD are more robust than behavioral response inhibition deficits and explain variance in response inhibition and ADHD severity. Although only affected participants with ADHD have deficient response inhibition, hypoactivation in inferior frontal and temporal-parietal nodes in unaffected siblings support the familial nature of the underlying neural process. Hypoactivation in these nodes may be useful as endophenotypes that extend beyond the affected individuals in the family. PMID:25615565
Optical imaging of neural and hemodynamic brain activity

NASA Astrophysics Data System (ADS)

Schei, Jennifer Lynn

Optical imaging technologies can be used to record neural and hemodynamic activity. Neural activity elicits physiological changes that alter the optical tissue properties. Specifically, changes in polarized light are concomitant with neural depolarization. We measured polarization changes from an isolated lobster nerve during action potential propagation using both reflected and transmitted light. In transmission mode, polarization changes were largest throughout the center of the nerve, suggesting that most of the optical signal arose from the inner nerve bundle. In reflection mode, polarization changes were largest near the edges, suggesting that most of the optical signal arose from the outer sheath. To overcome irregular cell orientation found in the brain, we measured polarization changes from a nerve tied in a knot. Our results show that neural activation produces polarization changes that can be imaged even without regular cell orientations. Neural activation expends energy resources and elicits metabolic delivery through blood vessel dilation, increasing blood flow and volume. We used spectroscopic imaging techniques combined with electrophysiological measurements to record evoked neural and hemodynamic responses from the auditory cortex of the rat. By using implantable optics, we measured responses across natural wake and sleep states, as well as responses following different amounts of sleep deprivation. During quiet sleep, evoked metabolic responses were larger compared to wake, perhaps because blood vessels were more compliant. When animals were sleep deprived, evoked hemodynamic responses were smaller following longer periods of deprivation. These results suggest that prolonged neural activity through sleep deprivation may diminish vascular compliance as indicated by the blunted vascular response. Subsequent sleep may allow vessels to relax, restoring their ability to deliver blood. These results also suggest that severe sleep deprivation or chronic sleep disturbances could push the vasculature to critical limits, leading to metabolic deficit and the potential for tissue trauma.
Development of a computational model on the neural activity patterns of a visual working memory in a hierarchical feedforward Network

NASA Astrophysics Data System (ADS)

An, Soyoung; Choi, Woochul; Paik, Se-Bum

2015-11-01

Understanding the mechanism of information processing in the human brain remains a unique challenge because the nonlinear interactions between the neurons in the network are extremely complex and because controlling every relevant parameter during an experiment is difficult. Therefore, a simulation using simplified computational models may be an effective approach. In the present study, we developed a general model of neural networks that can simulate nonlinear activity patterns in the hierarchical structure of a neural network system. To test our model, we first examined whether our simulation could match the previously-observed nonlinear features of neural activity patterns. Next, we performed a psychophysics experiment for a simple visual working memory task to evaluate whether the model could predict the performance of human subjects. Our studies show that the model is capable of reproducing the relationship between memory load and performance and may contribute, in part, to our understanding of how the structure of neural circuits can determine the nonlinear neural activity patterns in the human brain.
Atypical neural synchronization to speech envelope modulations in dyslexia.

PubMed

De Vos, Astrid; Vanvooren, Sophie; Vanderauwera, Jolijn; Ghesquière, Pol; Wouters, Jan

2017-01-01

A fundamental deficit in the synchronization of neural oscillations to temporal information in speech could underlie phonological processing problems in dyslexia. In this study, the hypothesis of a neural synchronization impairment is investigated more specifically as a function of different neural oscillatory bands and temporal information rates in speech. Auditory steady-state responses to 4, 10, 20 and 40Hz modulations were recorded in normal reading and dyslexic adolescents to measure neural synchronization of theta, alpha, beta and low-gamma oscillations to syllabic and phonemic rate information. In comparison to normal readers, dyslexic readers showed reduced non-synchronized theta activity, reduced synchronized alpha activity and enhanced synchronized beta activity. Positive correlations between alpha synchronization and phonological skills were found in normal readers, but were absent in dyslexic readers. In contrast, dyslexic readers exhibited positive correlations between beta synchronization and phonological skills. Together, these results suggest that auditory neural synchronization of alpha and beta oscillations is atypical in dyslexia, indicating deviant neural processing of both syllabic and phonemic rate information. Impaired synchronization of alpha oscillations in particular demonstrated to be the most prominent neural anomaly possibly hampering speech and phonological processing in dyslexic readers. Copyright © 2016 Elsevier Inc. All rights reserved.
GABA and Gap Junctions in the Development of Synchronized Activity in Human Pluripotent Stem Cell-Derived Neural Networks

PubMed Central

Mäkinen, Meeri Eeva-Liisa; Ylä-Outinen, Laura; Narkilahti, Susanna

2018-01-01

The electrical activity of the brain arises from single neurons communicating with each other. However, how single neurons interact during early development to give rise to neural network activity remains poorly understood. We studied the emergence of synchronous neural activity in human pluripotent stem cell (hPSC)-derived neural networks simultaneously on a single-neuron level and network level. The contribution of gamma-aminobutyric acid (GABA) and gap junctions to the development of synchronous activity in hPSC-derived neural networks was studied with GABA agonist and antagonist and by blocking gap junctional communication, respectively. We characterized the dynamics of the network-wide synchrony in hPSC-derived neural networks with high spatial resolution (calcium imaging) and temporal resolution microelectrode array (MEA). We found that the emergence of synchrony correlates with a decrease in very strong GABA excitation. However, the synchronous network was found to consist of a heterogeneous mixture of synchronously active cells with variable responses to GABA, GABA agonists and gap junction blockers. Furthermore, we show how single-cell distributions give rise to the network effect of GABA, GABA agonists and gap junction blockers. Finally, based on our observations, we suggest that the earliest form of synchronous neuronal activity depends on gap junctions and a decrease in GABA induced depolarization but not on GABAA mediated signaling. PMID:29559893
Different propagation speeds of recalled sequences in plastic spiking neural networks

NASA Astrophysics Data System (ADS)

Huang, Xuhui; Zheng, Zhigang; Hu, Gang; Wu, Si; Rasch, Malte J.

2015-03-01

Neural networks can generate spatiotemporal patterns of spike activity. Sequential activity learning and retrieval have been observed in many brain areas, and e.g. is crucial for coding of episodic memory in the hippocampus or generating temporal patterns during song production in birds. In a recent study, a sequential activity pattern was directly entrained onto the neural activity of the primary visual cortex (V1) of rats and subsequently successfully recalled by a local and transient trigger. It was observed that the speed of activity propagation in coordinates of the retinotopically organized neural tissue was constant during retrieval regardless how the speed of light stimulation sweeping across the visual field during training was varied. It is well known that spike-timing dependent plasticity (STDP) is a potential mechanism for embedding temporal sequences into neural network activity. How training and retrieval speeds relate to each other and how network and learning parameters influence retrieval speeds, however, is not well described. We here theoretically analyze sequential activity learning and retrieval in a recurrent neural network with realistic synaptic short-term dynamics and STDP. Testing multiple STDP rules, we confirm that sequence learning can be achieved by STDP. However, we found that a multiplicative nearest-neighbor (NN) weight update rule generated weight distributions and recall activities that best matched the experiments in V1. Using network simulations and mean-field analysis, we further investigated the learning mechanisms and the influence of network parameters on recall speeds. Our analysis suggests that a multiplicative STDP rule with dominant NN spike interaction might be implemented in V1 since recall speed was almost constant in an NMDA-dominant regime. Interestingly, in an AMPA-dominant regime, neural circuits might exhibit recall speeds that instead follow the change in stimulus speeds. This prediction could be tested in experiments.
Functional connectivity of the rodent brain using optical imaging

NASA Astrophysics Data System (ADS)

Guevara Codina, Edgar

The aim of this thesis is to apply functional connectivity in a variety of animal models, using several optical imaging modalities. Even at rest, the brain shows high metabolic activity: the correlation in slow spontaneous fluctuations identifies remotely connected areas of the brain; hence the term "functional connectivity". Ongoing changes in spontaneous activity may provide insight into the neural processing that takes most of the brain metabolic activity, and so may provide a vast source of disease related changes. Brain hemodynamics may be modified during disease and affect resting-state activity. The thesis aims to better understand these changes in functional connectivity due to disease, using functional optical imaging. The optical imaging techniques explored in the first two contributions of this thesis are Optical Imaging of Intrinsic Signals and Laser Speckle Contrast Imaging, together they can estimate the metabolic rate of oxygen consumption, that closely parallels neural activity. They both have adequate spatial and temporal resolution and are well adapted to image the convexity of the mouse cortex. In the last article, a depth-sensitive modality called photoacoustic tomography was used in the newborn rat. Optical coherence tomography and laminar optical tomography were also part of the array of imaging techniques developed and applied in other collaborations. The first article of this work shows the changes in functional connectivity in an acute murine model of epileptiform activity. Homologous correlations are both increased and decreased with a small dependence on seizure duration. These changes suggest a potential decoupling between the hemodynamic parameters in resting-state networks, underlining the importance to investigate epileptic networks with several independent hemodynamic measures. The second study examines a novel murine model of arterial stiffness: the unilateral calcification of the right carotid. Seed-based connectivity analysis showed a decreasing trend of homologous correlation in the motor and cingulate cortices. Graph analyses showed a randomization of the cortex functional networks, suggesting a loss of connectivity, more specifically in the motor cortex ipsilateral to the treated carotid; however these changes are not reflected in differentiated metabolic estimates. Confounds remain due to the fact that carotid rigidification gives rise to neural decline in the hippocampus as well as unilateral alteration of vascular pulsatility; however the results support the need to look at several hemodynamic parameters when imaging the brain after arterial remodeling. The third article of this thesis studies a model of inflammatory injury on the newborn rat. Oxygen saturation and functional connectivity were assessed with photoacoustic tomography. Oxygen saturation was decreased in the site of the lesion and on the cortex ipsilateral to the injury; however this decrease is not fully explained by hypovascularization revealed by histology. Seed-based functional connectivity analysis showed that inter-hemispheric connectivity is not affected by inflammatory injury.
Correlation of neural activity with behavioral kinematics reveals distinct sensory encoding and evidence accumulation processes during active tactile sensing.

PubMed

Delis, Ioannis; Dmochowski, Jacek P; Sajda, Paul; Wang, Qi

2018-07-15

Many real-world decisions rely on active sensing, a dynamic process for directing our sensors (e.g. eyes or fingers) across a stimulus to maximize information gain. Though ecologically pervasive, limited work has focused on identifying neural correlates of the active sensing process. In tactile perception, we often make decisions about an object/surface by actively exploring its shape/texture. Here we investigate the neural correlates of active tactile decision-making by simultaneously measuring electroencephalography (EEG) and finger kinematics while subjects interrogated a haptic surface to make perceptual judgments. Since sensorimotor behavior underlies decision formation in active sensing tasks, we hypothesized that the neural correlates of decision-related processes would be detectable by relating active sensing to neural activity. Novel brain-behavior correlation analysis revealed that three distinct EEG components, localizing to right-lateralized occipital cortex (LOC), middle frontal gyrus (MFG), and supplementary motor area (SMA), respectively, were coupled with active sensing as their activity significantly correlated with finger kinematics. To probe the functional role of these components, we fit their single-trial-couplings to decision-making performance using a hierarchical-drift-diffusion-model (HDDM), revealing that the LOC modulated the encoding of the tactile stimulus whereas the MFG predicted the rate of information integration towards a choice. Interestingly, the MFG disappeared from components uncovered from control subjects performing active sensing but not required to make perceptual decisions. By uncovering the neural correlates of distinct stimulus encoding and evidence accumulation processes, this study delineated, for the first time, the functional role of cortical areas in active tactile decision-making. Copyright © 2018 Elsevier Inc. All rights reserved.
Maximum entropy models as a tool for building precise neural controls.

PubMed

Savin, Cristina; Tkačik, Gašper

2017-10-01

Neural responses are highly structured, with population activity restricted to a small subset of the astronomical range of possible activity patterns. Characterizing these statistical regularities is important for understanding circuit computation, but challenging in practice. Here we review recent approaches based on the maximum entropy principle used for quantifying collective behavior in neural activity. We highlight recent models that capture population-level statistics of neural data, yielding insights into the organization of the neural code and its biological substrate. Furthermore, the MaxEnt framework provides a general recipe for constructing surrogate ensembles that preserve aspects of the data, but are otherwise maximally unstructured. This idea can be used to generate a hierarchy of controls against which rigorous statistical tests are possible. Copyright © 2017 Elsevier Ltd. All rights reserved.
Time of Day Differences in Neural Reward Functioning in Healthy Young Men.

PubMed

Byrne, Jamie E M; Hughes, Matthew E; Rossell, Susan L; Johnson, Sheri L; Murray, Greg

2017-09-13

Reward function appears to be modulated by the circadian system, but little is known about the neural basis of this interaction. Previous research suggests that the neural reward response may be different in the afternoon; however, the direction of this effect is contentious. Reward response may follow the diurnal rhythm in self-reported positive affect, peaking in the early afternoon. An alternative is that daily reward response represents a type of prediction error, with neural reward activation relatively high at times of day when rewards are unexpected (i.e., early and late in the day). The present study measured neural reward activation in the context of a validated reward task at 10.00 h, 14.00 h, and 19.00 h in healthy human males. A region of interest BOLD fMRI protocol was used to investigate the diurnal waveform of activation in reward-related brain regions. Multilevel modeling found, as expected, a highly significant quadratic time-of-day effect focusing on the left putamen ( p < 0.001). Consistent with the "prediction error" hypothesis, activation was significantly higher at 10.00 h and 19.00 h compared with 14.00 h. It is provisionally concluded that the putamen may be particularly important in endogenous priming of reward motivation at different times of day, with the pattern of activation consistent with circadian-modulated reward expectancies in neural pathways (i.e., greater activation to reward stimuli at unexpected times of day). This study encourages further research into circadian modulation of reward and underscores the methodological importance of accounting for time of day in fMRI protocols. SIGNIFICANCE STATEMENT This is one of the first studies to use a repeated-measures imaging procedure to explore the diurnal rhythm of reward activation. Although self-reported reward (most often operationalized as positive affect) peaks in the afternoon, the present findings indicate that neural activation is lowest at this time. We conclude that the diurnal neural activation pattern may reflect a prediction error of the brain, where rewards at unexpected times (10.00 h and 19.00 h) elicit higher activation in reward brain regions than at expected (14.00 h) times. These data also have methodological significance, suggesting that there may be a time of day influence, which should be accounted for in neural reward studies. Copyright © 2017 the authors 0270-6474/17/378895-06$15.00/0.
Exogenous (automatic) attention to emotional stimuli: a review.

PubMed

Carretié, Luis

2014-12-01

Current knowledge on the architecture of exogenous attention (also called automatic, bottom-up, or stimulus-driven attention, among other terms) has been mainly obtained from studies employing neutral, anodyne stimuli. Since, from an evolutionary perspective, exogenous attention can be understood as an adaptive tool for rapidly detecting salient events, reorienting processing resources to them, and enhancing processing mechanisms, emotional events (which are, by definition, salient for the individual) would seem crucial to a comprehensive understanding of this process. This review, focusing on the visual modality, describes 55 experiments in which both emotional and neutral irrelevant distractors are presented at the same time as ongoing task targets. Qualitative and, when possible, meta-analytic descriptions of results are provided. The most conspicuous result is that, as confirmed by behavioral and/or neural indices, emotional distractors capture exogenous attention to a significantly greater extent than do neutral distractors. The modulatory effects of the nature of distractors capturing attention, of the ongoing task characteristics, and of individual differences, previously proposed as mediating factors, are also described. Additionally, studies reviewed here provide temporal and spatial information-partially absent in traditional cognitive models-on the neural basis of preattention/evaluation, reorienting, and sensory amplification, the main subprocesses involved in exogenous attention. A model integrating these different levels of information is proposed. The present review, which reveals that there are several key issues for which experimental data are surprisingly scarce, confirms the relevance of including emotional distractors in studies on exogenous attention.
Mapping the brain correlates of borderline personality disorder: A functional neuroimaging meta-analysis of resting state studies.

PubMed

Visintin, Eleonora; De Panfilis, Chiara; Amore, Mario; Balestrieri, Matteo; Wolf, Robert Christian; Sambataro, Fabio

2016-11-01

Altered intrinsic function of the brain has been implicated in Borderline Personality Disorder (BPD). Nonetheless, imaging studies have yielded inconsistent alterations of brain function. To investigate the neural activity at rest in BPD, we conducted a set of meta-analyses of brain imaging studies performed at rest. A total of seven functional imaging studies (152 patients with BPD and 147 control subjects) were combined using whole-brain Signed Differential Mapping meta-analyses. Furthermore, two conjunction meta-analyses of neural activity at rest were also performed: with neural activity changes during emotional processing, and with structural differences, respectively. We found altered neural activity in the regions of the default mode network (DMN) in BPD. Within the regions of the midline core DMN, patients with BPD showed greater activity in the anterior as well as in the posterior midline hubs relative to controls. Conversely, in the regions of the dorsal DMN they showed reduced activity compared to controls in the right lateral temporal complex and bilaterally in the orbitofrontal cortex. Increased activity in the precuneus was observed both at rest and during emotional processing. Reduced neural activity at rest in lateral temporal complex was associated with smaller volume of this area. Heterogeneity across imaging studies. Altered activity in the regions of the midline core as well as of the dorsal subsystem of the DMN may reflect difficulties with interpersonal and affective regulation in BPD. These findings suggest that changes in spontaneous neural activity could underlie core symptoms in BPD. Copyright © 2016 Elsevier B.V. All rights reserved.
ERPS to Monitor Non-conscious Mentation

NASA Technical Reports Server (NTRS)

Donchin, E.

1984-01-01

Event Related Brain Potentials (or ERPs) are extracted from the EEG that can be recorded between a pair of electrodes placed on a person's scalp. The EEG is recorded as a continual fluctuation in voltage. It is the results of the integration of the potential fields generated by a multitude of neuronal ensembles that are active as the brain goes about its business. Within this ongoing signal it is possible to distinguish voltage fluctuations that are triggered in neural structures by the occurrence of specific events. This activity, evoked as it is by an external event, is known as the Evoked, or Event Related, Potential. The ERPs provide a unique opportunity to monitor non-conscious mentation. The inferences that can be based on ERP data are described and the limits of these inferences are emphasized. This, however, will not be an exhaustive review of the use of ERPs in Engineering Psychology. The application, its scope, and its limitations will be illustrated by means of one example. This example is preceded by a brief technical introduction to the methodology used in the study of ERPs. The manner in which ERPs are used to study cognition is described.
Oscillatory magnetic brain activity is related to dissociative symptoms and childhood adversities - A study in women with multiple trauma.

PubMed

Schalinski, I; Moran, J K; Elbert, T; Reindl, V; Wienbruch, C

2017-08-15

Individuals with trauma-related disorders are complex and heterogeneous; part of this complexity derives from additional psychopathology like dissociation as well as environmental adversities such as traumatic stress, experienced throughout the lifespan. Understanding the neurophysiological abnormalities in Post-traumatic stress disorder (PTSD) requires a simultaneous consideration of these factors. Resting state magnetoencephalography (MEG) recordings were obtained from 41 women with PTSD and comorbid depressive symptoms, and 16 healthy women. Oscillatory brain activity was extracted for five frequency bands and 11 source locations, and analyzed in relation to shutdown dissociation and adversity-related measures. Dissociative symptoms were related to increased delta and lowered beta power. Adversity-related measures modulated theta and alpha oscillatory power (in particular childhood sexual abuse) and differed between patients and controls. Findings are based on women with comorbid depressive symptoms and therefore may not be applicable for men or groups with other clinical profiles. In respect to childhood adversities, we had no reliable source for the early infancy. Trauma-related abnormalities in neural organization vary with both exposure to adversities as well as their potential to evoke ongoing shutdown responses. Copyright © 2017 Elsevier B.V. All rights reserved.

Rapid whole brain imaging of neural activity in freely behaving larval zebrafish (Danio rerio)

PubMed Central

Shang, Chunfeng; Yang, Wenbin; Bai, Lu; Du, Jiulin

2017-01-01

The internal brain dynamics that link sensation and action are arguably better studied during natural animal behaviors. Here, we report on a novel volume imaging and 3D tracking technique that monitors whole brain neural activity in freely swimming larval zebrafish (Danio rerio). We demonstrated the capability of our system through functional imaging of neural activity during visually evoked and prey capture behaviors in larval zebrafish. PMID:28930070
Neural Activity During Health Messaging Predicts Reductions in Smoking Above and Beyond Self-Report

PubMed Central

Falk, Emily B.; Berkman, Elliot T.; Whalen, Danielle; Lieberman, Matthew D.

2011-01-01

Objective The current study tested whether neural activity in response to messages designed to help smokers quit could predict smoking reduction, above and beyond self-report. Design Using neural activity in an a priori region of interest (a subregion of medial prefrontal cortex [MPFC]), in response to ads designed to help smokers quit smoking, we prospectively predicted reductions in smoking in a community sample of smokers (N = 28) who were attempting to quit smoking. Smoking was assessed via expired carbon monoxide (CO; a biological measure of recent smoking) at baseline and 1 month following exposure to professionally developed quitting ads. Results A positive relationship was observed between activity in the MPFC region of interest and successful quitting (increased activity in MPFC was associated with a greater decrease in expired CO). The addition of neural activity to a model predicting changes in CO from self-reported intentions, self-efficacy, and ability to relate to the messages significantly improved model fit, doubling the variance explained ( Rself−report2=.15,Rself−report+neuralactivity2=.35,Rchange2=.20). Conclusion: Neural activity is a useful complement to existing self-report measures. In this investigation, we extend prior work predicting behavior change based on neural activity in response to persuasive media to an important health domain and discuss potential psychological interpretations of the brain–behavior link. Our results support a novel use of neuroimaging technology for understanding the psychology of behavior change and facilitating health promotion. PMID:21261410
Selective Estrogen Receptor Modulation Increases Hippocampal Activity during Probabilistic Association Learning in Schizophrenia

PubMed Central

Kindler, Jochen; Weickert, Cynthia Shannon; Skilleter, Ashley J; Catts, Stanley V; Lenroot, Rhoshel; Weickert, Thomas W

2015-01-01

People with schizophrenia show probabilistic association learning impairment in conjunction with abnormal neural activity. The selective estrogen receptor modulator (SERM) raloxifene preserves neural activity during memory in healthy older men and improves memory in schizophrenia. Here, we tested the extent to which raloxifene modifies neural activity during learning in schizophrenia. Nineteen people with schizophrenia participated in a twelve-week randomized, double-blind, placebo-controlled, cross-over adjunctive treatment trial of the SERM raloxifene administered orally at 120 mg daily to assess brain activity during probabilistic association learning using functional magnetic resonance imaging (fMRI). Raloxifene improved probabilistic association learning and significantly increased fMRI BOLD activity in the hippocampus and parahippocampal gyrus relative to placebo. A separate region of interest confirmatory analysis in 21 patients vs 36 healthy controls showed a positive association between parahippocampal neural activity and learning in patients, but no such relationship in the parahippocampal gyrus of healthy controls. Thus, selective estrogen receptor modulation by raloxifene concurrently increases activity in the parahippocampal gyrus and improves probabilistic association learning in schizophrenia. These results support a role for estrogen receptor modulation of mesial temporal lobe neural activity in the remediation of learning disabilities in both men and women with schizophrenia. PMID:25829142
THE FUNCTIONAL ARCHITECTURE OF DEHYDRATION-ANOREXIA

PubMed Central

Watts, Alan G.; Boyle, Christina N.

2010-01-01

The anorexia that accompanies the drinking of hypertonic saline (DE-anorexia) is a critical adaptive behavioral mechanism that helps protect the integrity of fluid compartments during extended periods of cellular dehydration. Feeding is rapidly reinstated once drinking water is made available again. The relative simplicity and reproducibility of these behaviors makes DE-anorexia a very useful model for investigating how the various neural networks that control ingestive behaviors first suppress and then reinstate feeding. We show that DE-anorexia develops primarily because the mechanisms that terminate ongoing meals are upregulated in such a way as to significantly reduce meal size. At the same time however, signals generated by the ensuing negative energy balance appropriately activate neural mechanisms that can increase food intake. But as the output from these two competing processes is integrated, the net result is an increasing reduction of nocturnal food intake, despite the fact that spontaneous meals are initiated with the same frequency as in control animals. Furthermore, hypothalamic NPY injections also stimulate feeding in DE-anorexic animals with the same latency as controls, but again meals are prematurely terminated. Comparing Fos expression patterns across the brain following 2-deoxyglucose administration to control and DE-anorexic animals implicates neurons in the descending part of the parvicellular paraventricular nucleus of the hypothalamus and the lateral hypothalamic areas as key components of the networks that control DE-anorexia. Finally, DE-anorexia generates multiple inhibitory processes to suppress feeding. These are differentially disengaged once drinking water is reinstated. PMID:20399797
The Neural Correlates of Race

PubMed Central

Ito, Tiffany A.; Bartholow, Bruce D.

2009-01-01

Behavioral analyses are a natural choice for understanding the wide-ranging behavioral consequences of racial stereotyping and prejudice. However, neuroimaging and electrophysiological research has recently considered the neural mechanisms that underlie racial categorization and the activation and application of racial stereotypes and prejudice, revealing exciting new insights. Work reviewed here points to the importance of neural structures previously associated with face processing, semantic knowledge activation, evaluation, and self-regulatory behavioral control, allowing for the specification of a neural model of race processing. We show how research on the neural correlates of race can serve to link otherwise disparate lines of evidence on the neural underpinnings of a broad array of social-cognitive phenomena, and consider implications for effecting change in race relations. PMID:19896410
The optimization of force inputs for active structural acoustic control using a neural network

NASA Technical Reports Server (NTRS)

Cabell, R. H.; Lester, H. C.; Silcox, R. J.

1992-01-01

This paper investigates the use of a neural network to determine which force actuators, of a multi-actuator array, are best activated in order to achieve structural-acoustic control. The concept is demonstrated using a cylinder/cavity model on which the control forces, produced by piezoelectric actuators, are applied with the objective of reducing the interior noise. A two-layer neural network is employed and the back propagation solution is compared with the results calculated by a conventional, least-squares optimization analysis. The ability of the neural network to accurately and efficiently control actuator activation for interior noise reduction is demonstrated.
Implementation of an Adaptive Controller System from Concept to Flight Test

NASA Technical Reports Server (NTRS)

Larson, Richard R.; Burken, John J.; Butler, Bradley S.; Yokum, Steve

2009-01-01

The National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) is conducting ongoing flight research using adaptive controller algorithms. A highly modified McDonnell-Douglas NF-15B airplane called the F-15 Intelligent Flight Control System (IFCS) is used to test and develop these algorithms. Modifications to this airplane include adding canards and changing the flight control systems to interface a single-string research controller processor for neural network algorithms. Research goals include demonstration of revolutionary control approaches that can efficiently optimize aircraft performance in both normal and failure conditions and advancement of neural-network-based flight control technology for new aerospace system designs. This report presents an overview of the processes utilized to develop adaptive controller algorithms during a flight-test program, including a description of initial adaptive controller concepts and a discussion of modeling formulation and performance testing. Design finalization led to integration with the system interfaces, verification of the software, validation of the hardware to the requirements, design of failure detection, development of safety limiters to minimize the effect of erroneous neural network commands, and creation of flight test control room displays to maximize human situational awareness; these are also discussed.
Altered Synchronizations among Neural Networks in Geriatric Depression

PubMed Central

Wang, Lihong; Chou, Ying-Hui; Potter, Guy G.; Steffens, David C.

2015-01-01

Although major depression has been considered as a manifestation of discoordinated activity between affective and cognitive neural networks, only a few studies have examined the relationships among neural networks directly. Because of the known disconnection theory, geriatric depression could be a useful model in studying the interactions among different networks. In the present study, using independent component analysis to identify intrinsically connected neural networks, we investigated the alterations in synchronizations among neural networks in geriatric depression to better understand the underlying neural mechanisms. Resting-state fMRI data was collected from thirty-two patients with geriatric depression and thirty-two age-matched never-depressed controls. We compared the resting-state activities between the two groups in the default-mode, central executive, attention, salience, and affective networks as well as correlations among these networks. The depression group showed stronger activity than the controls in an affective network, specifically within the orbitofrontal region. However, unlike the never-depressed controls, geriatric depression group lacked synchronized/antisynchronized activity between the affective network and the other networks. Those depressed patients with lower executive function has greater synchronization between the salience network with the executive and affective networks. Our results demonstrate the effectiveness of the between-network analyses in examining neural models for geriatric depression. PMID:26180795
Altered Synchronizations among Neural Networks in Geriatric Depression.

PubMed

Wang, Lihong; Chou, Ying-Hui; Potter, Guy G; Steffens, David C

2015-01-01

Although major depression has been considered as a manifestation of discoordinated activity between affective and cognitive neural networks, only a few studies have examined the relationships among neural networks directly. Because of the known disconnection theory, geriatric depression could be a useful model in studying the interactions among different networks. In the present study, using independent component analysis to identify intrinsically connected neural networks, we investigated the alterations in synchronizations among neural networks in geriatric depression to better understand the underlying neural mechanisms. Resting-state fMRI data was collected from thirty-two patients with geriatric depression and thirty-two age-matched never-depressed controls. We compared the resting-state activities between the two groups in the default-mode, central executive, attention, salience, and affective networks as well as correlations among these networks. The depression group showed stronger activity than the controls in an affective network, specifically within the orbitofrontal region. However, unlike the never-depressed controls, geriatric depression group lacked synchronized/antisynchronized activity between the affective network and the other networks. Those depressed patients with lower executive function has greater synchronization between the salience network with the executive and affective networks. Our results demonstrate the effectiveness of the between-network analyses in examining neural models for geriatric depression.
Novel four-sided neural probe fabricated by a thermal lamination process of polymer films.

PubMed

Shin, Soowon; Kim, Jae-Hyun; Jeong, Joonsoo; Gwon, Tae Mok; Lee, Seung-Hee; Kim, Sung June

2017-02-15

Ideally, neural probes should have channels with a three-dimensional (3-D) configuration to record the activities of 3-D neural circuits. Many types of 3-D neural probes have been developed; however, most of them were designed as an array of multiple shanks with electrodes located along one side of the shanks. We developed a novel liquid crystal polymer (LCP)-based neural probe with four-sided electrodes. This probe has electrodes on four sides of the shank, i.e., the front, back and two sidewalls. To generate the proposed configuration of the electrodes, we used a thermal lamination process involving LCP films and laser micromachining. The proposed novel four-sided neural probe, was used to successfully perform in vivo multichannel neural recording in the mouse primary somatosensory cortex. The multichannel neural recording showed that the proposed four-sided neural probe can record spiking activities from a more diverse neuronal population than single-sided probes. This was confirmed by a pairwise Pearson correlation coefficient (Pearson's r) analysis and a cross-correlation analysis. The developed four-sided neural probe can be used to record various signals from a complex neural network. Copyright © 2016 Elsevier B.V. All rights reserved.
Self-organization of synchronous activity propagation in neuronal networks driven by local excitation

PubMed Central

Bayati, Mehdi; Valizadeh, Alireza; Abbassian, Abdolhossein; Cheng, Sen

2015-01-01

Many experimental and theoretical studies have suggested that the reliable propagation of synchronous neural activity is crucial for neural information processing. The propagation of synchronous firing activity in so-called synfire chains has been studied extensively in feed-forward networks of spiking neurons. However, it remains unclear how such neural activity could emerge in recurrent neuronal networks through synaptic plasticity. In this study, we investigate whether local excitation, i.e., neurons that fire at a higher frequency than the other, spontaneously active neurons in the network, can shape a network to allow for synchronous activity propagation. We use two-dimensional, locally connected and heterogeneous neuronal networks with spike-timing dependent plasticity (STDP). We find that, in our model, local excitation drives profound network changes within seconds. In the emergent network, neural activity propagates synchronously through the network. This activity originates from the site of the local excitation and propagates through the network. The synchronous activity propagation persists, even when the local excitation is removed, since it derives from the synaptic weight matrix. Importantly, once this connectivity is established it remains stable even in the presence of spontaneous activity. Our results suggest that synfire-chain-like activity can emerge in a relatively simple way in realistic neural networks by locally exciting the desired origin of the neuronal sequence. PMID:26089794
Enhanced responses of lumbar superficial dorsal horn neurons to intradermal PAR-2 agonist but not histamine in a mouse hindpaw dry skin itch model

PubMed Central

Akiyama, Tasuku; Carstens, Mirela Iodi

2011-01-01

Chronic itch is symptomatic of many skin conditions and systemic diseases. Little is known about pathophysiological alterations in itch-signaling neural pathways associated with chronic itch. We used a mouse model of hindpaw chronic dry skin itch to investigate properties of presumptive itch-signaling neurons. Neurons in the lumbar superficial dorsal horn ipsilateral to hindpaw dry skin treatment exhibited a high level of spontaneous activity that was inhibited by scratching the plantar surface. Most spontaneously active units exhibited further increases in firing rate following intradermal injection of an agonist of the protease-activated receptor PAR-2, or histamine. The large majority of pruritogen-responsive units also responded to capsaicin and allyl isothiocyanate. For neurons ipsilateral to dry skin treatment, responses elicited by the PAR-2 agonist, but not histamine or mechanical stimuli, were significantly larger compared with neurons ipsilateral to vehicle (water) treatment or neurons recorded in naïve (untreated) mice. The spontaneous activity may signal ongoing itch, while enhanced PAR-2 agonist-evoked responses may underlie hyperknesis (enhanced itch), both of which are symptomatic of many chronic itch conditions. The enhancement of neuronal responses evoked by the PAR-2 agonist, but not by histamine or mechanical stimuli, implies that the dry skin condition selectively sensitized PAR-2 agonist-sensitive primary afferent pruriceptors. PMID:21430273
Enhanced responses of lumbar superficial dorsal horn neurons to intradermal PAR-2 agonist but not histamine in a mouse hindpaw dry skin itch model.

PubMed

Akiyama, Tasuku; Carstens, Mirela Iodi; Carstens, E

2011-06-01

Chronic itch is symptomatic of many skin conditions and systemic diseases. Little is known about pathophysiological alterations in itch-signaling neural pathways associated with chronic itch. We used a mouse model of hindpaw chronic dry skin itch to investigate properties of presumptive itch-signaling neurons. Neurons in the lumbar superficial dorsal horn ipsilateral to hindpaw dry skin treatment exhibited a high level of spontaneous activity that was inhibited by scratching the plantar surface. Most spontaneously active units exhibited further increases in firing rate following intradermal injection of an agonist of the protease-activated receptor PAR-2, or histamine. The large majority of pruritogen-responsive units also responded to capsaicin and allyl isothiocyanate. For neurons ipsilateral to dry skin treatment, responses elicited by the PAR-2 agonist, but not histamine or mechanical stimuli, were significantly larger compared with neurons ipsilateral to vehicle (water) treatment or neurons recorded in naïve (untreated) mice. The spontaneous activity may signal ongoing itch, while enhanced PAR-2 agonist-evoked responses may underlie hyperknesis (enhanced itch), both of which are symptomatic of many chronic itch conditions. The enhancement of neuronal responses evoked by the PAR-2 agonist, but not by histamine or mechanical stimuli, implies that the dry skin condition selectively sensitized PAR-2 agonist-sensitive primary afferent pruriceptors.
Towards a magnetoresistive platform for neural signal recording

NASA Astrophysics Data System (ADS)

Sharma, P. P.; Gervasoni, G.; Albisetti, E.; D'Ercoli, F.; Monticelli, M.; Moretti, D.; Forte, N.; Rocchi, A.; Ferrari, G.; Baldelli, P.; Sampietro, M.; Benfenati, F.; Bertacco, R.; Petti, D.

2017-05-01

A promising strategy to get deeper insight on brain functionalities relies on the investigation of neural activities at the cellular and sub-cellular level. In this framework, methods for recording neuron electrical activity have gained interest over the years. Main technological challenges are associated to finding highly sensitive detection schemes, providing considerable spatial and temporal resolution. Moreover, the possibility to perform non-invasive assays would constitute a noteworthy benefit. In this work, we present a magnetoresistive platform for the detection of the action potential propagation in neural cells. Such platform allows, in perspective, the in vitro recording of neural signals arising from single neurons, neural networks and brain slices.
State-dependent, bidirectional modulation of neural network activity by endocannabinoids.

PubMed

Piet, Richard; Garenne, André; Farrugia, Fanny; Le Masson, Gwendal; Marsicano, Giovanni; Chavis, Pascale; Manzoni, Olivier J

2011-11-16

The endocannabinoid (eCB) system and the cannabinoid CB1 receptor (CB1R) play key roles in the modulation of brain functions. Although actions of eCBs and CB1Rs are well described at the synaptic level, little is known of their modulation of neural activity at the network level. Using microelectrode arrays, we have examined the role of CB1R activation in the modulation of the electrical activity of rat and mice cortical neural networks in vitro. We find that exogenous activation of CB1Rs expressed on glutamatergic neurons decreases the spontaneous activity of cortical neural networks. Moreover, we observe that the net effect of the CB1R antagonist AM251 inversely correlates with the initial level of activity in the network: blocking CB1Rs increases network activity when basal network activity is low, whereas it depresses spontaneous activity when its initial level is high. Our results reveal a complex role of CB1Rs in shaping spontaneous network activity, and suggest that the outcome of endogenous neuromodulation on network function might be state dependent.
Trial-by-Trial Motor Cortical Correlates of a Rapidly Adapting Visuomotor Internal Model.

PubMed

Stavisky, Sergey D; Kao, Jonathan C; Ryu, Stephen I; Shenoy, Krishna V

2017-02-15

Accurate motor control is mediated by internal models of how neural activity generates movement. We examined neural correlates of an adapting internal model of visuomotor gain in motor cortex while two macaques performed a reaching task in which the gain scaling between the hand and a presented cursor was varied. Previous studies of cortical changes during visuomotor adaptation focused on preparatory and perimovement epochs and analyzed trial-averaged neural data. Here, we recorded simultaneous neural population activity using multielectrode arrays and focused our analysis on neural differences in the period before the target appeared. We found that we could estimate the monkey's internal model of the gain using the neural population state during this pretarget epoch. This neural correlate depended on the gain experienced during recent trials and it predicted the speed of the subsequent reach. To explore the utility of this internal model estimate for brain-machine interfaces, we performed an offline analysis showing that it can be used to compensate for upcoming reach extent errors. Together, these results demonstrate that pretarget neural activity in motor cortex reflects the monkey's internal model of visuomotor gain on single trials and can potentially be used to improve neural prostheses. SIGNIFICANCE STATEMENT When generating movement commands, the brain is believed to use internal models of the relationship between neural activity and the body's movement. Visuomotor adaptation tasks have revealed neural correlates of these computations in multiple brain areas during movement preparation and execution. Here, we describe motor cortical changes in a visuomotor gain change task even before a specific movement is cued. We were able to estimate the gain internal model from these pretarget neural correlates and relate it to single-trial behavior. This is an important step toward understanding the sensorimotor system's algorithms for updating its internal models after specific movements and errors. Furthermore, the ability to estimate the internal model before movement could improve motor neural prostheses being developed for people with paralysis. Copyright © 2017 the authors 0270-6474/17/371721-12$15.00/0.
Why Some People Discount More than Others: Baseline Activation in the Dorsal PFC Mediates the Link between COMT Genotype and Impatient Choice

PubMed Central

Gianotti, Lorena R. R.; Figner, Bernd; Ebstein, Richard P.; Knoch, Daria

2012-01-01

Individuals differ widely in how steeply they discount future rewards. The sources of these stable individual differences in delay discounting (DD) are largely unknown. One candidate is the COMT Val158Met polymorphism, known to modulate prefrontal dopamine levels and affect DD. To identify possible neural mechanisms by which this polymorphism may contribute to stable individual DD differences, we measured 73 participants’ neural baseline activation using resting electroencephalogram (EEG). Such neural baseline activation measures are highly heritable and stable over time, thus an ideal endophenotype candidate to explain how genes may influence behavior via individual differences in neural function. After EEG-recording, participants made a series of incentive-compatible intertemporal choices to determine the steepness of their DD. We found that COMT significantly affected DD and that this effect was mediated by baseline activation level in the left dorsal prefrontal cortex (DPFC): (i) COMT had a significant effect on DD such that the number of Val alleles was positively correlated with steeper DD (higher numbers of Val alleles means greater COMT activity and thus lower dopamine levels). (ii) A whole-brain search identified a cluster in left DPFC where baseline activation was correlated with DD; lower activation was associated with steeper DD. (iii) COMT had a significant effect on the baseline activation level in this left DPFC cluster such that a higher number of Val alleles was associated with lower baseline activation. (iv) The effect of COMT on DD was explained by the mediating effect of neural baseline activation in the left DPFC cluster. Our study thus establishes baseline activation level in left DPFC as salient neural signature in the form of an endophenotype that mediates the link between COMT and DD. PMID:22586360
The brain as a dynamic physical system.

PubMed

McKenna, T M; McMullen, T A; Shlesinger, M F

1994-06-01

The brain is a dynamic system that is non-linear at multiple levels of analysis. Characterization of its non-linear dynamics is fundamental to our understanding of brain function. Identifying families of attractors in phase space analysis, an approach which has proven valuable in describing non-linear mechanical and electrical systems, can prove valuable in describing a range of behaviors and associated neural activity including sensory and motor repertoires. Additionally, transitions between attractors may serve as useful descriptors for analysing state changes in neurons and neural ensembles. Recent observations of synchronous neural activity, and the emerging capability to record the spatiotemporal dynamics of neural activity by voltage-sensitive dyes and electrode arrays, provide opportunities for observing the population dynamics of neural ensembles within a dynamic systems context. New developments in the experimental physics of complex systems, such as the control of chaotic systems, selection of attractors, attractor switching and transient states, can be a source of powerful new analytical tools and insights into the dynamics of neural systems.
Practical approximation method for firing-rate models of coupled neural networks with correlated inputs

NASA Astrophysics Data System (ADS)

Barreiro, Andrea K.; Ly, Cheng

2017-08-01

Rapid experimental advances now enable simultaneous electrophysiological recording of neural activity at single-cell resolution across large regions of the nervous system. Models of this neural network activity will necessarily increase in size and complexity, thus increasing the computational cost of simulating them and the challenge of analyzing them. Here we present a method to approximate the activity and firing statistics of a general firing rate network model (of the Wilson-Cowan type) subject to noisy correlated background inputs. The method requires solving a system of transcendental equations and is fast compared to Monte Carlo simulations of coupled stochastic differential equations. We implement the method with several examples of coupled neural networks and show that the results are quantitatively accurate even with moderate coupling strengths and an appreciable amount of heterogeneity in many parameters. This work should be useful for investigating how various neural attributes qualitatively affect the spiking statistics of coupled neural networks.
Unpacking the neural associations of emotion and judgment in emotion-congruent judgment

PubMed Central

Beer, Jennifer S.

2012-01-01

The current study takes a new approach to understand the neural systems that support emotion-congruent judgment. The bulk of previous neural research has inferred emotional influences on judgment from disadvantageous judgments or non-random individual differences. The current study manipulated the influence of emotional information on judgments of stimuli that were equivocally composed of positive and negative attributes. Emotion-congruent processing was operationalized in two ways: neural activation significantly associated with primes that lead to emotionally congruent judgments and neural activation significantly associated with judgments that were preceded by emotionally congruent primes. Distinct regions of medial orbitofrontal cortex were associated with these patterns of emotion-congruent processing. Judgments that were incongruent with preceding primes were associated with dorsomedial prefrontal cortex, ventrolateral prefrontal cortex and lateral orbitofrontal cortex activity. The current study demonstrates a new approach to investigate the neural systems associated with emotion-congruent judgment. The findings suggest that medial OFC may support attentional processes that underlie emotion-congruent judgment. PMID:21511825

Wnt/Yes-Associated Protein Interactions During Neural Tissue Patterning of Human Induced Pluripotent Stem Cells.

PubMed

Bejoy, Julie; Song, Liqing; Zhou, Yi; Li, Yan

2018-04-01

Human induced pluripotent stem cells (hiPSCs) have special ability to self-assemble into neural spheroids or mini-brain-like structures. During the self-assembly process, Wnt signaling plays an important role in regional patterning and establishing positional identity of hiPSC-derived neural progenitors. Recently, the role of Wnt signaling in regulating Yes-associated protein (YAP) expression (nuclear or cytoplasmic), the pivotal regulator during organ growth and tissue generation, has attracted increasing interests. However, the interactions between Wnt and YAP expression for neural lineage commitment of hiPSCs remain poorly explored. The objective of this study is to investigate the effects of Wnt signaling and YAP expression on the cellular population in three-dimensional (3D) neural spheroids derived from hiPSCs. In this study, Wnt signaling was activated using CHIR99021 for 3D neural spheroids derived from human iPSK3 cells through embryoid body formation. Our results indicate that Wnt activation induces nuclear localization of YAP and upregulates the expression of HOXB4, the marker for hindbrain/spinal cord. By contrast, the cells exhibit more rostral forebrain neural identity (expression of TBR1) without Wnt activation. Cytochalasin D was then used to induce cytoplasmic YAP and the results showed the decreased HOXB4 expression. In addition, the incorporation of microparticles in the neural spheroids was investigated for the perturbation of neural patterning. This study may indicate the bidirectional interactions of Wnt signaling and YAP expression during neural tissue patterning, which have the significance in neurological disease modeling, drug screening, and neural tissue regeneration.
Risky Decision Making in Neurofibromatosis Type 1: An Exploratory Study.

PubMed

Jonas, Rachel K; Roh, EunJi; Montojo, Caroline A; Pacheco, Laura A; Rosser, Tena; Silva, Alcino J; Bearden, Carrie E

2017-03-01

Neurofibromatosis type 1 (NF1) is a monogenic disorder affecting cognitive function. About one third of children with NF1 have attentional disorders, and the cognitive phenotype is characterized by impairment in prefrontally-mediated functions. Mouse models of NF1 show irregularities in GABA release and striatal dopamine metabolism. We hypothesized that youth with NF1 would show abnormal behavior and neural activity on a task of risk-taking reliant on prefrontal-striatal circuits. Youth with NF1 (N=29) and demographically comparable healthy controls (N=22), ages 8-19, were administered a developmentally sensitive gambling task, in which they chose between low-risk gambles with a high probability of obtaining a small reward, and high-risk gambles with a low probability of obtaining a large reward. We used functional magnetic resonance imaging (fMRI) to investigate neural activity associated with risky decision making, as well as age-associated changes in these behavioral and neural processes. Behaviorally, youth with NF1 tended to make fewer risky decisions than controls. Neuroimaging analyses revealed significantly reduced neural activity across multiple brain regions involved in higher-order semantic processing and motivation (i.e., anterior cingulate, paracingulate, supramarginal, and angular gyri) in patients with NF1 relative to controls during the task. We also observed atypical age-associated changes in neural activity in patients with NF1, such that during risk taking, neural activity tended to decrease with age in controls, whereas it tended to increase with age in patients with NF1. Findings suggest that developmental trajectories of neural activity during risky decision-making may be disrupted in youth with NF1.
Neural activation toward erotic stimuli in homosexual and heterosexual males.

PubMed

Kagerer, Sabine; Klucken, Tim; Wehrum, Sina; Zimmermann, Mark; Schienle, Anne; Walter, Bertram; Vaitl, Dieter; Stark, Rudolf

2011-11-01

Studies investigating sexual arousal exist, yet there are diverging findings on the underlying neural mechanisms with regard to sexual orientation. Moreover, sexual arousal effects have often been confounded with general arousal effects. Hence, it is still unclear which structures underlie the sexual arousal response in homosexual and heterosexual men. Neural activity and subjective responses were investigated in order to disentangle sexual from general arousal. Considering sexual orientation, differential and conjoint neural activations were of interest. The functional magnetic resonance imaging (fMRI) study focused on the neural networks involved in the processing of sexual stimuli in 21 male participants (11 homosexual, 10 heterosexual). Both groups viewed pictures with erotic content as well as aversive and neutral stimuli. The erotic pictures were subdivided into three categories (most sexually arousing, least sexually arousing, and rest) based on the individual subjective ratings of each participant. Blood oxygen level-dependent responses measured by fMRI and subjective ratings. A conjunction analysis revealed conjoint neural activation related to sexual arousal in thalamus, hypothalamus, occipital cortex, and nucleus accumbens. Increased insula, amygdala, and anterior cingulate gyrus activation could be linked to general arousal. Group differences emerged neither when viewing the most sexually arousing pictures compared with highly arousing aversive pictures nor compared with neutral pictures. Results suggest that a widespread neural network is activated by highly sexually arousing visual stimuli. A partly distinct network of structures underlies sexual and general arousal effects. The processing of preferred, highly sexually arousing stimuli recruited similar structures in homosexual and heterosexual males. © 2011 International Society for Sexual Medicine.
Traumatic brain injury causes long-term behavioral changes related to region-specific increases of cerebral blood flow.

PubMed

Pöttker, Bruno; Stöber, Franziska; Hummel, Regina; Angenstein, Frank; Radyushkin, Konstantin; Goldschmidt, Jürgen; Schäfer, Michael K E

2017-12-01

Traumatic brain injury (TBI) is a leading cause of disability and death and survivors often suffer from long-lasting motor impairment, cognitive deficits, anxiety disorders and epilepsy. Few experimental studies have investigated long-term sequelae after TBI and relations between behavioral changes and neural activity patterns remain elusive. We examined these issues in a murine model of TBI combining histology, behavioral analyses and single-photon emission computed tomography (SPECT) imaging of regional cerebral blood flow (CBF) as a proxy for neural activity. Adult C57Bl/6N mice were subjected to unilateral cortical impact injury and investigated at early (15-57 days after lesion, dal) and late (184-225 dal) post-traumatic time points. TBI caused pronounced tissue loss of the parietal cortex and subcortical structures and enduring neurological deficits. Marked perilesional astro- and microgliosis was found at 57 dal and declined at 225 dal. Motor and gait pattern deficits occurred at early time points after TBI and improved over the time. In contrast, impaired performance in the Morris water maze test and decreased anxiety-like behavior persisted together with an increased susceptibility to pentylenetetrazole-induced seizures suggesting alterations in neural activity patterns. Accordingly, SPECT imaging of CBF indicated asymmetric hemispheric baseline neural activity patterns. In the ipsilateral hemisphere, increased baseline neural activity was found in the amygdala. In the contralateral hemisphere, homotopic to the structural brain damage, the hippocampus and distinct cortex regions displayed increased baseline neural activity. Thus, regionally elevated CBF along with behavioral alterations indicate that increased neural activity is critically involved in the long-lasting consequences of TBI.
Feedback modulation of neural network synchrony and seizure susceptibility by Mdm2-p53-Nedd4-2 signaling.

PubMed

Jewett, Kathryn A; Christian, Catherine A; Bacos, Jonathan T; Lee, Kwan Young; Zhu, Jiuhe; Tsai, Nien-Pei

2016-03-22

Neural network synchrony is a critical factor in regulating information transmission through the nervous system. Improperly regulated neural network synchrony is implicated in pathophysiological conditions such as epilepsy. Despite the awareness of its importance, the molecular signaling underlying the regulation of neural network synchrony, especially after stimulation, remains largely unknown. In this study, we show that elevation of neuronal activity by the GABA(A) receptor antagonist, Picrotoxin, increases neural network synchrony in primary mouse cortical neuron cultures. The elevation of neuronal activity triggers Mdm2-dependent degradation of the tumor suppressor p53. We show here that blocking the degradation of p53 further enhances Picrotoxin-induced neural network synchrony, while promoting the inhibition of p53 with a p53 inhibitor reduces Picrotoxin-induced neural network synchrony. These data suggest that Mdm2-p53 signaling mediates a feedback mechanism to fine-tune neural network synchrony after activity stimulation. Furthermore, genetically reducing the expression of a direct target gene of p53, Nedd4-2, elevates neural network synchrony basally and occludes the effect of Picrotoxin. Finally, using a kainic acid-induced seizure model in mice, we show that alterations of Mdm2-p53-Nedd4-2 signaling affect seizure susceptibility. Together, our findings elucidate a critical role of Mdm2-p53-Nedd4-2 signaling underlying the regulation of neural network synchrony and seizure susceptibility and reveal potential therapeutic targets for hyperexcitability-associated neurological disorders.
In vitro and in vivo analysis and characterization of engineered spinal neural implants (Conference Presentation)

NASA Astrophysics Data System (ADS)

Shor, Erez; Shoham, Shy; Levenberg, Shulamit

2016-03-01

Spinal cord injury is a devastating medical condition. Recent developments in pre-clinical and clinical research have started to yield neural implants inducing functional recovery after spinal cord transection injury. However, the functional performance of the transplants was assessed using histology and behavioral experiments which are unable to study cell dynamics and the therapeutic response. Here, we use neurophotonic tools and optogenetic probes to investigate cellular level morphology and activity characteristics of neural implants over time at the cellular level. These methods were used in-vitro and in-vivo, in a mouse spinal cord injury implant model. Following previous attempts to induce recovery after spinal cord injury, we engineered a pre-vascularized implant to obtain better functional performance. To image network activity of a construct implanted in a mouse spinal cord, we transfected the implant to express GCaMP6 calcium activity indicators and implanted these constructs under a spinal cord chamber enabling 2-photon chronic in vivo neural activity imaging. Activity and morphology analysis image processing software was developed to automatically quantify the behavior of the neural and vascular networks. Our experimental results and analyses demonstrate that vascularized and non-vascularized constructs exhibit very different morphologic and activity patterns at the cellular level. This work enables further optimization of neural implants and also provides valuable tools for continuous cellular level monitoring and evaluation of transplants designed for various neurodegenerative disease models.
Abnormal neural activities of directional brain networks in patients with long-term bilateral hearing loss.

PubMed

Xu, Long-Chun; Zhang, Gang; Zou, Yue; Zhang, Min-Feng; Zhang, Dong-Sheng; Ma, Hua; Zhao, Wen-Bo; Zhang, Guang-Yu

2017-10-13

The objective of the study is to provide some implications for rehabilitation of hearing impairment by investigating changes of neural activities of directional brain networks in patients with long-term bilateral hearing loss. Firstly, we implemented neuropsychological tests of 21 subjects (11 patients with long-term bilateral hearing loss, and 10 subjects with normal hearing), and these tests revealed significant differences between the deaf group and the controls. Then we constructed the individual specific virtual brain based on functional magnetic resonance data of participants by utilizing effective connectivity and multivariate regression methods. We exerted the stimulating signal to the primary auditory cortices of the virtual brain and observed the brain region activations. We found that patients with long-term bilateral hearing loss presented weaker brain region activations in the auditory and language networks, but enhanced neural activities in the default mode network as compared with normally hearing subjects. Especially, the right cerebral hemisphere presented more changes than the left. Additionally, weaker neural activities in the primary auditor cortices were also strongly associated with poorer cognitive performance. Finally, causal analysis revealed several interactional circuits among activated brain regions, and these interregional causal interactions implied that abnormal neural activities of the directional brain networks in the deaf patients impacted cognitive function.
Neural substrates related to auditory working memory comparisons in dyslexia: An fMRI study

PubMed Central

CONWAY, TIM; HEILMAN, KENNETH M.; GOPINATH, KAUNDINYA; PECK, KYUNG; BAUER, RUSSELL; BRIGGS, RICHARD W.; TORGESEN, JOSEPH K.; CROSSON, BRUCE

2010-01-01

Adult readers with developmental phonological dyslexia exhibit significant difficulty comparing pseudowords and pure tones in auditory working memory (AWM). This suggests deficient AWM skills for adults diagnosed with dyslexia. Despite behavioral differences, it is unknown whether neural substrates of AWM differ between adults diagnosed with dyslexia and normal readers. Prior neuroimaging of adults diagnosed with dyslexia and normal readers, and post-mortem findings of neural structural anomalies in adults diagnosed with dyslexia support the hypothesis of atypical neural activity in temporoparietal and inferior frontal regions during AWM tasks in adults diagnosed with dyslexia. We used fMRI during two binaural AWM tasks (pseudowords or pure tones comparisons) in adults diagnosed with dyslexia (n = 11) and normal readers (n = 11). For both AWM tasks, adults diagnosed with dyslexia exhibited greater activity in left posterior superior temporal (BA 22) and inferior parietal regions (BA 40) than normal readers. Comparing neural activity between groups and between stimuli contrasts (pseudowords vs. tones), adults diagnosed with dyslexia showed greater primary auditory cortex activity (BA 42; tones > pseudowords) than normal readers. Thus, greater activity in primary auditory, posterior superior temporal, and inferior parietal cortices during linguistic and non-linguistic AWM tasks for adults diagnosed with dyslexia compared to normal readers indicate differences in neural substrates of AWM comparison tasks. PMID:18577292
Long-Latency Reductions in Gamma Power Predict Hemodynamic Changes That Underlie the Negative BOLD Signal

PubMed Central

Harris, Samuel; Bruyns-Haylett, Michael; Kennerley, Aneurin; Zheng, Ying; Martin, Chris; Jones, Myles; Redgrave, Peter; Berwick, Jason

2015-01-01

Studies that use prolonged periods of sensory stimulation report associations between regional reductions in neural activity and negative blood oxygenation level-dependent (BOLD) signaling. However, the neural generators of the negative BOLD response remain to be characterized. Here, we use single-impulse electrical stimulation of the whisker pad in the anesthetized rat to identify components of the neural response that are related to “negative” hemodynamic changes in the brain. Laminar multiunit activity and local field potential recordings of neural activity were performed concurrently with two-dimensional optical imaging spectroscopy measuring hemodynamic changes. Repeated measurements over multiple stimulation trials revealed significant variations in neural responses across session and animal datasets. Within this variation, we found robust long-latency decreases (300 and 2000 ms after stimulus presentation) in gamma-band power (30–80 Hz) in the middle-superficial cortical layers in regions surrounding the activated whisker barrel cortex. This reduction in gamma frequency activity was associated with corresponding decreases in the hemodynamic responses that drive the negative BOLD signal. These findings suggest a close relationship between BOLD responses and neural events that operate over time scales that outlast the initiating sensory stimulus, and provide important insights into the neurophysiological basis of negative neuroimaging signals. PMID:25788681
Race modulates neural activity during imitation

PubMed Central

Losin, Elizabeth A. Reynolds; Iacoboni, Marco; Martin, Alia; Cross, Katy A.; Dapretto, Mirella

2014-01-01

Imitation plays a central role in the acquisition of culture. People preferentially imitate others who are self-similar, prestigious or successful. Because race can indicate a person's self-similarity or status, race influences whom people imitate. Prior studies of the neural underpinnings of imitation have not considered the effects of race. Here we measured neural activity with fMRI while European American participants imitated meaningless gestures performed by actors of their own race, and two racial outgroups, African American, and Chinese American. Participants also passively observed the actions of these actors and their portraits. Frontal, parietal and occipital areas were differentially activated while participants imitated actors of different races. More activity was present when imitating African Americans than the other racial groups, perhaps reflecting participants' reported lack of experience with and negative attitudes towards this group, or the group's lower perceived social status. This pattern of neural activity was not found when participants passively observed the gestures of the actors or simply looked at their faces. Instead, during face-viewing neural responses were overall greater for own-race individuals, consistent with prior race perception studies not involving imitation. Our findings represent a first step in elucidating neural mechanisms involved in cultural learning, a process that influences almost every aspect of our lives but has thus far received little neuroscientific study. PMID:22062193
Unscented Kalman Filter for Brain-Machine Interfaces

PubMed Central

Li, Zheng; O'Doherty, Joseph E.; Hanson, Timothy L.; Lebedev, Mikhail A.; Henriquez, Craig S.; Nicolelis, Miguel A. L.

2009-01-01

Brain machine interfaces (BMIs) are devices that convert neural signals into commands to directly control artificial actuators, such as limb prostheses. Previous real-time methods applied to decoding behavioral commands from the activity of populations of neurons have generally relied upon linear models of neural tuning and were limited in the way they used the abundant statistical information contained in the movement profiles of motor tasks. Here, we propose an n-th order unscented Kalman filter which implements two key features: (1) use of a non-linear (quadratic) model of neural tuning which describes neural activity significantly better than commonly-used linear tuning models, and (2) augmentation of the movement state variables with a history of n-1 recent states, which improves prediction of the desired command even before incorporating neural activity information and allows the tuning model to capture relationships between neural activity and movement at multiple time offsets simultaneously. This new filter was tested in BMI experiments in which rhesus monkeys used their cortical activity, recorded through chronically implanted multielectrode arrays, to directly control computer cursors. The 10th order unscented Kalman filter outperformed the standard Kalman filter and the Wiener filter in both off-line reconstruction of movement trajectories and real-time, closed-loop BMI operation. PMID:19603074
Long-latency reductions in gamma power predict hemodynamic changes that underlie the negative BOLD signal.

PubMed

Boorman, Luke; Harris, Samuel; Bruyns-Haylett, Michael; Kennerley, Aneurin; Zheng, Ying; Martin, Chris; Jones, Myles; Redgrave, Peter; Berwick, Jason

2015-03-18

Studies that use prolonged periods of sensory stimulation report associations between regional reductions in neural activity and negative blood oxygenation level-dependent (BOLD) signaling. However, the neural generators of the negative BOLD response remain to be characterized. Here, we use single-impulse electrical stimulation of the whisker pad in the anesthetized rat to identify components of the neural response that are related to "negative" hemodynamic changes in the brain. Laminar multiunit activity and local field potential recordings of neural activity were performed concurrently with two-dimensional optical imaging spectroscopy measuring hemodynamic changes. Repeated measurements over multiple stimulation trials revealed significant variations in neural responses across session and animal datasets. Within this variation, we found robust long-latency decreases (300 and 2000 ms after stimulus presentation) in gamma-band power (30-80 Hz) in the middle-superficial cortical layers in regions surrounding the activated whisker barrel cortex. This reduction in gamma frequency activity was associated with corresponding decreases in the hemodynamic responses that drive the negative BOLD signal. These findings suggest a close relationship between BOLD responses and neural events that operate over time scales that outlast the initiating sensory stimulus, and provide important insights into the neurophysiological basis of negative neuroimaging signals. Copyright © 2015 Boorman et al.
1/f neural noise and electrophysiological indices of contextual prediction in aging.

PubMed

Dave, S; Brothers, T A; Swaab, T Y

2018-07-15

Prediction of upcoming words during reading has been suggested to enhance the efficiency of discourse processing. Emerging models have postulated that predictive mechanisms require synchronous firing of neural networks, but to date, this relationship has been investigated primarily through oscillatory activity in narrow frequency bands. A recently-developed measure proposed to reflect broadband neural activity - and thereby synchronous neuronal firing - is 1/f neural noise extracted from EEG spectral power. Previous research has indicated that this measure of 1/f neural noise changes across the lifespan, and these neural changes predict age-related behavioral impairments in visual working memory. Using a cross-sectional sample of young and older adults, we examined age-related changes in 1/f neural noise and whether this measure predicted ERP correlates of successful lexical prediction during discourse comprehension. 1/f neural noise across two different language tasks revealed high within-subject correlations, indicating that this measure can provide a reliable index of individualized patterns of neural activation. In addition to age, 1/f noise was a significant predictor of N400 effects of successful lexical prediction; however, noise did not mediate age-related declines in other ERP effects. We discuss broader implications of these findings for theories of predictive processing, as well as potential applications of 1/f noise across research populations. Copyright © 2018 Elsevier B.V. All rights reserved.
The Effects of GABAergic Polarity Changes on Episodic Neural Network Activity in Developing Neural Systems.

PubMed

Blanco, Wilfredo; Bertram, Richard; Tabak, Joël

2017-01-01

Early in development, neural systems have primarily excitatory coupling, where even GABAergic synapses are excitatory. Many of these systems exhibit spontaneous episodes of activity that have been characterized through both experimental and computational studies. As development progress the neural system goes through many changes, including synaptic remodeling, intrinsic plasticity in the ion channel expression, and a transformation of GABAergic synapses from excitatory to inhibitory. What effect each of these, and other, changes have on the network behavior is hard to know from experimental studies since they all happen in parallel. One advantage of a computational approach is that one has the ability to study developmental changes in isolation. Here, we examine the effects of GABAergic synapse polarity change on the spontaneous activity of both a mean field and a neural network model that has both glutamatergic and GABAergic coupling, representative of a developing neural network. We find some intuitive behavioral changes as the GABAergic neurons go from excitatory to inhibitory, shared by both models, such as a decrease in the duration of episodes. We also find some paradoxical changes in the activity that are only present in the neural network model. In particular, we find that during early development the inter-episode durations become longer on average, while later in development they become shorter. In addressing this unexpected finding, we uncover a priming effect that is particularly important for a small subset of neurons, called the "intermediate neurons." We characterize these neurons and demonstrate why they are crucial to episode initiation, and why the paradoxical behavioral change result from priming of these neurons. The study illustrates how even arguably the simplest of developmental changes that occurs in neural systems can present non-intuitive behaviors. It also makes predictions about neural network behavioral changes that occur during development that may be observable even in actual neural systems where these changes are convoluted with changes in synaptic connectivity and intrinsic neural plasticity.
Localizing Tortoise Nests by Neural Networks.

PubMed

Barbuti, Roberto; Chessa, Stefano; Micheli, Alessio; Pucci, Rita

2016-01-01

The goal of this research is to recognize the nest digging activity of tortoises using a device mounted atop the tortoise carapace. The device classifies tortoise movements in order to discriminate between nest digging, and non-digging activity (specifically walking and eating). Accelerometer data was collected from devices attached to the carapace of a number of tortoises during their two-month nesting period. Our system uses an accelerometer and an activity recognition system (ARS) which is modularly structured using an artificial neural network and an output filter. For the purpose of experiment and comparison, and with the aim of minimizing the computational cost, the artificial neural network has been modelled according to three different architectures based on the input delay neural network (IDNN). We show that the ARS can achieve very high accuracy on segments of data sequences, with an extremely small neural network that can be embedded in programmable low power devices. Given that digging is typically a long activity (up to two hours), the application of ARS on data segments can be repeated over time to set up a reliable and efficient system, called Tortoise@, for digging activity recognition.
Irrational exuberance and neural crash warning signals during endogenous experimental market bubbles

PubMed Central

Smith, Alec; Lohrenz, Terry; King, Justin; Montague, P. Read; Camerer, Colin F.

2014-01-01

Groups of humans routinely misassign value to complex future events, especially in settings involving the exchange of resources. If properly structured, experimental markets can act as excellent probes of human group-level valuation mechanisms during pathological overvaluations—price bubbles. The connection between the behavioral and neural underpinnings of such phenomena has been absent, in part due to a lack of enabling technology. We used a multisubject functional MRI paradigm to measure neural activity in human subjects participating in experimental asset markets in which endogenous price bubbles formed and crashed. Although many ideas exist about how and why such bubbles may form and how to identify them, our experiment provided a window on the connection between neural responses and behavioral acts (buying and selling) that created the bubbles. We show that aggregate neural activity in the nucleus accumbens (NAcc) tracks the price bubble and that NAcc activity aggregated within a market predicts future price changes and crashes. Furthermore, the lowest-earning subjects express a stronger tendency to buy as a function of measured NAcc activity. Conversely, we report a signal in the anterior insular cortex in the highest earners that precedes the impending price peak, is associated with a higher propensity to sell in high earners, and that may represent a neural early warning signal in these subjects. Such markets could be a model system to understand neural and behavior mechanisms in other settings where emergent group-level activity exhibits mistaken belief or valuation. PMID:25002476
Irrational exuberance and neural crash warning signals during endogenous experimental market bubbles.

PubMed

Smith, Alec; Lohrenz, Terry; King, Justin; Montague, P Read; Camerer, Colin F

2014-07-22

Groups of humans routinely misassign value to complex future events, especially in settings involving the exchange of resources. If properly structured, experimental markets can act as excellent probes of human group-level valuation mechanisms during pathological overvaluations--price bubbles. The connection between the behavioral and neural underpinnings of such phenomena has been absent, in part due to a lack of enabling technology. We used a multisubject functional MRI paradigm to measure neural activity in human subjects participating in experimental asset markets in which endogenous price bubbles formed and crashed. Although many ideas exist about how and why such bubbles may form and how to identify them, our experiment provided a window on the connection between neural responses and behavioral acts (buying and selling) that created the bubbles. We show that aggregate neural activity in the nucleus accumbens (NAcc) tracks the price bubble and that NAcc activity aggregated within a market predicts future price changes and crashes. Furthermore, the lowest-earning subjects express a stronger tendency to buy as a function of measured NAcc activity. Conversely, we report a signal in the anterior insular cortex in the highest earners that precedes the impending price peak, is associated with a higher propensity to sell in high earners, and that may represent a neural early warning signal in these subjects. Such markets could be a model system to understand neural and behavior mechanisms in other settings where emergent group-level activity exhibits mistaken belief or valuation.
Multi-scale, multi-modal analysis uncovers complex relationship at the brain tissue-implant neural interface: new emphasis on the biological interface

NASA Astrophysics Data System (ADS)

Michelson, Nicholas J.; Vazquez, Alberto L.; Eles, James R.; Salatino, Joseph W.; Purcell, Erin K.; Williams, Jordan J.; Cui, X. Tracy; Kozai, Takashi D. Y.

2018-06-01

Objective. Implantable neural electrode devices are important tools for neuroscience research and have an increasing range of clinical applications. However, the intricacies of the biological response after implantation, and their ultimate impact on recording performance, remain challenging to elucidate. Establishing a relationship between the neurobiology and chronic recording performance is confounded by technical challenges related to traditional electrophysiological, material, and histological limitations. This can greatly impact the interpretations of results pertaining to device performance and tissue health surrounding the implant. Approach. In this work, electrophysiological activity and immunohistological analysis are compared after controlling for motion artifacts, quiescent neuronal activity, and material failure of devices in order to better understand the relationship between histology and electrophysiological outcomes. Main results. Even after carefully accounting for these factors, the presence of viable neurons and lack of glial scarring does not convey single unit recording performance. Significance. To better understand the biological factors influencing neural activity, detailed cellular and molecular tissue responses were examined. Decreases in neural activity and blood oxygenation in the tissue surrounding the implant, shift in expression levels of vesicular transporter proteins and ion channels, axon and myelin injury, and interrupted blood flow in nearby capillaries can impact neural activity around implanted neural interfaces. Combined, these tissue changes highlight the need for more comprehensive, basic science research to elucidate the relationship between biology and chronic electrophysiology performance in order to advance neural technologies.
A Decline in Response Variability Improves Neural Signal Detection during Auditory Task Performance.

PubMed

von Trapp, Gardiner; Buran, Bradley N; Sen, Kamal; Semple, Malcolm N; Sanes, Dan H

2016-10-26

The detection of a sensory stimulus arises from a significant change in neural activity, but a sensory neuron's response is rarely identical to successive presentations of the same stimulus. Large trial-to-trial variability would limit the central nervous system's ability to reliably detect a stimulus, presumably affecting perceptual performance. However, if response variability were to decrease while firing rate remained constant, then neural sensitivity could improve. Here, we asked whether engagement in an auditory detection task can modulate response variability, thereby increasing neural sensitivity. We recorded telemetrically from the core auditory cortex of gerbils, both while they engaged in an amplitude-modulation detection task and while they sat quietly listening to the identical stimuli. Using a signal detection theory framework, we found that neural sensitivity was improved during task performance, and this improvement was closely associated with a decrease in response variability. Moreover, units with the greatest change in response variability had absolute neural thresholds most closely aligned with simultaneously measured perceptual thresholds. Our findings suggest that the limitations imposed by response variability diminish during task performance, thereby improving the sensitivity of neural encoding and potentially leading to better perceptual sensitivity. The detection of a sensory stimulus arises from a significant change in neural activity. However, trial-to-trial variability of the neural response may limit perceptual performance. If the neural response to a stimulus is quite variable, then the response on a given trial could be confused with the pattern of neural activity generated when the stimulus is absent. Therefore, a neural mechanism that served to reduce response variability would allow for better stimulus detection. By recording from the cortex of freely moving animals engaged in an auditory detection task, we found that variability of the neural response becomes smaller during task performance, thereby improving neural detection thresholds. Copyright © 2016 the authors 0270-6474/16/3611097-10$15.00/0.
A Decline in Response Variability Improves Neural Signal Detection during Auditory Task Performance

PubMed Central

Buran, Bradley N.; Sen, Kamal; Semple, Malcolm N.; Sanes, Dan H.

2016-01-01

The detection of a sensory stimulus arises from a significant change in neural activity, but a sensory neuron's response is rarely identical to successive presentations of the same stimulus. Large trial-to-trial variability would limit the central nervous system's ability to reliably detect a stimulus, presumably affecting perceptual performance. However, if response variability were to decrease while firing rate remained constant, then neural sensitivity could improve. Here, we asked whether engagement in an auditory detection task can modulate response variability, thereby increasing neural sensitivity. We recorded telemetrically from the core auditory cortex of gerbils, both while they engaged in an amplitude-modulation detection task and while they sat quietly listening to the identical stimuli. Using a signal detection theory framework, we found that neural sensitivity was improved during task performance, and this improvement was closely associated with a decrease in response variability. Moreover, units with the greatest change in response variability had absolute neural thresholds most closely aligned with simultaneously measured perceptual thresholds. Our findings suggest that the limitations imposed by response variability diminish during task performance, thereby improving the sensitivity of neural encoding and potentially leading to better perceptual sensitivity. SIGNIFICANCE STATEMENT The detection of a sensory stimulus arises from a significant change in neural activity. However, trial-to-trial variability of the neural response may limit perceptual performance. If the neural response to a stimulus is quite variable, then the response on a given trial could be confused with the pattern of neural activity generated when the stimulus is absent. Therefore, a neural mechanism that served to reduce response variability would allow for better stimulus detection. By recording from the cortex of freely moving animals engaged in an auditory detection task, we found that variability of the neural response becomes smaller during task performance, thereby improving neural detection thresholds. PMID:27798189

Close-Packed Silicon Microelectrodes for Scalable Spatially Oversampled Neural Recording

PubMed Central

Scholvin, Jörg; Kinney, Justin P.; Bernstein, Jacob G.; Moore-Kochlacs, Caroline; Kopell, Nancy; Fonstad, Clifton G.; Boyden, Edward S.

2015-01-01

Objective Neural recording electrodes are important tools for understanding neural codes and brain dynamics. Neural electrodes that are close-packed, such as in tetrodes, enable spatial oversampling of neural activity, which facilitates data analysis. Here we present the design and implementation of close-packed silicon microelectrodes, to enable spatially oversampled recording of neural activity in a scalable fashion. Methods Our probes are fabricated in a hybrid lithography process, resulting in a dense array of recording sites connected to submicron dimension wiring. Results We demonstrate an implementation of a probe comprising 1000 electrode pads, each 9 × 9 μm, at a pitch of 11 μm. We introduce design automation and packaging methods that allow us to readily create a large variety of different designs. Significance Finally, we perform neural recordings with such probes in the live mammalian brain that illustrate the spatial oversampling potential of closely packed electrode sites. PMID:26699649
Model Of Neural Network With Creative Dynamics

NASA Technical Reports Server (NTRS)

Zak, Michail; Barhen, Jacob

1993-01-01

Paper presents analysis of mathematical model of one-neuron/one-synapse neural network featuring coupled activation and learning dynamics and parametrical periodic excitation. Demonstrates self-programming, partly random behavior of suitable designed neural network; believed to be related to spontaneity and creativity of biological neural networks.
Subliminal versus supraliminal stimuli activate neural responses in anterior cingulate cortex, fusiform gyrus and insula: a meta-analysis of fMRI studies.

PubMed

Meneguzzo, Paolo; Tsakiris, Manos; Schioth, Helgi B; Stein, Dan J; Brooks, Samantha J

2014-01-01

Non-conscious neural activation may underlie various psychological functions in health and disorder. However, the neural substrates of non-conscious processing have not been entirely elucidated. Examining the differential effects of arousing stimuli that are consciously, versus unconsciously perceived will improve our knowledge of neural circuitry involved in non-conscious perception. Here we conduct preliminary analyses of neural activation in studies that have used both subliminal and supraliminal presentation of the same stimulus. We use Activation Likelihood Estimation (ALE) to examine functional Magnetic Resonance Imaging (fMRI) studies that uniquely present the same stimuli subliminally and supraliminally to healthy participants during functional magnetic resonance imaging (fMRI). We included a total of 193 foci from 9 studies representing subliminal stimulation and 315 foci from 10 studies representing supraliminal stimulation. The anterior cingulate cortex is significantly activated during both subliminal and supraliminal stimulus presentation. Subliminal stimuli are linked to significantly increased activation in the right fusiform gyrus and right insula. Supraliminal stimuli show significantly increased activation in the left rostral anterior cingulate. Non-conscious processing of arousing stimuli may involve primary visual areas and may also recruit the insula, a brain area involved in eventual interoceptive awareness. The anterior cingulate is perhaps a key brain region for the integration of conscious and non-conscious processing. These preliminary data provide candidate brain regions for further study in to the neural correlates of conscious experience.
Fractal Patterns of Neural Activity Exist within the Suprachiasmatic Nucleus and Require Extrinsic Network Interactions

PubMed Central

Hu, Kun; Meijer, Johanna H.; Shea, Steven A.; vanderLeest, Henk Tjebbe; Pittman-Polletta, Benjamin; Houben, Thijs; van Oosterhout, Floor; Deboer, Tom; Scheer, Frank A. J. L.

2012-01-01

The mammalian central circadian pacemaker (the suprachiasmatic nucleus, SCN) contains thousands of neurons that are coupled through a complex network of interactions. In addition to the established role of the SCN in generating rhythms of ∼24 hours in many physiological functions, the SCN was recently shown to be necessary for normal self-similar/fractal organization of motor activity and heart rate over a wide range of time scales—from minutes to 24 hours. To test whether the neural network within the SCN is sufficient to generate such fractal patterns, we studied multi-unit neural activity of in vivo and in vitro SCNs in rodents. In vivo SCN-neural activity exhibited fractal patterns that are virtually identical in mice and rats and are similar to those in motor activity at time scales from minutes up to 10 hours. In addition, these patterns remained unchanged when the main afferent signal to the SCN, namely light, was removed. However, the fractal patterns of SCN-neural activity are not autonomous within the SCN as these patterns completely broke down in the isolated in vitro SCN despite persistence of circadian rhythmicity. Thus, SCN-neural activity is fractal in the intact organism and these fractal patterns require network interactions between the SCN and extra-SCN nodes. Such a fractal control network could underlie the fractal regulation observed in many physiological functions that involve the SCN, including motor control and heart rate regulation. PMID:23185285
Early neural activation during facial affect processing in adolescents with Autism Spectrum Disorder.

PubMed

Leung, Rachel C; Pang, Elizabeth W; Cassel, Daniel; Brian, Jessica A; Smith, Mary Lou; Taylor, Margot J

2015-01-01

Impaired social interaction is one of the hallmarks of Autism Spectrum Disorder (ASD). Emotional faces are arguably the most critical visual social stimuli and the ability to perceive, recognize, and interpret emotions is central to social interaction and communication, and subsequently healthy social development. However, our understanding of the neural and cognitive mechanisms underlying emotional face processing in adolescents with ASD is limited. We recruited 48 adolescents, 24 with high functioning ASD and 24 typically developing controls. Participants completed an implicit emotional face processing task in the MEG. We examined spatiotemporal differences in neural activation between the groups during implicit angry and happy face processing. While there were no differences in response latencies between groups across emotions, adolescents with ASD had lower accuracy on the implicit emotional face processing task when the trials included angry faces. MEG data showed atypical neural activity in adolescents with ASD during angry and happy face processing, which included atypical activity in the insula, anterior and posterior cingulate and temporal and orbitofrontal regions. Our findings demonstrate differences in neural activity during happy and angry face processing between adolescents with and without ASD. These differences in activation in social cognitive regions may index the difficulties in face processing and in comprehension of social reward and punishment in the ASD group. Thus, our results suggest that atypical neural activation contributes to impaired affect processing, and thus social cognition, in adolescents with ASD.
Altered neural activation during prepotent response inhibition in breast cancer survivors treated with chemotherapy: an fMRI study.

PubMed

Kam, Julia W Y; Boyd, Lara A; Hsu, Chun L; Liu-Ambrose, Teresa; Handy, Todd C; Lim, Howard J; Hayden, Sherri; Campbell, Kristin L

2016-09-01

While impairments in executive functions have been reported in breast cancer survivors (BCS) who have undergone adjuvant chemotherapy, only a limited number of functional neuroimaging studies have associated alterations in cerebral activity with executive functions deficits in BCS. Using fMRI, the current study assessed the neural basis underlying a specific facet of executive function, namely prepotent response inhibition. 12 BCS who self-reported cognitive problems up to 3 years following cancer treatment and 12 female healthy comparisons (HC) performed the Stroop task. We compared their neural activation between the incongruent and neutral experimental conditions. Relative to the HC group, BCS showed lower blood-oxygen level dependent signal in several frontal regions, including the anterior cingulate cortex, a region critical for response inhibition. Our data indicates reduced neural activation in BCS during a prepotent response inhibition task, providing support for the prevailing notion of neural alterations observed in BCS treated with chemotherapy.
Differences in Neural Correlates of Speech Perception in 3 Month Olds at High and Low Risk for Autism Spectrum Disorder.

PubMed

Edwards, Laura A; Wagner, Jennifer B; Tager-Flusberg, Helen; Nelson, Charles A

2017-10-01

In this study, we investigated neural precursors of language acquisition as potential endophenotypes of autism spectrum disorder (ASD) in 3-month-old infants at high and low familial ASD risk. Infants were imaged using functional near-infrared spectroscopy while they listened to auditory stimuli containing syllable repetitions; their neural responses were analyzed over left and right temporal regions. While female low risk infants showed initial neural activation that decreased over exposure to repetition-based stimuli, potentially indicating a habituation response to repetition in speech, female high risk infants showed no changes in neural activity over exposure. This finding may indicate a potential neural endophenotype of language development or ASD specific to females at risk for the disorder.
Contextual Processing of Abstract Concepts Reveals Neural Representations of Non-Linguistic Semantic Content

PubMed Central

Wilson-Mendenhall, Christine D.; Simmons, W. Kyle; Martin, Alex; Barsalou, Lawrence W.

2014-01-01

Concepts develop for many aspects of experience, including abstract internal states and abstract social activities that do not refer to concrete entities in the world. The current study assessed the hypothesis that, like concrete concepts, distributed neural patterns of relevant, non-linguistic semantic content represent the meanings of abstract concepts. In a novel neuroimaging paradigm, participants processed two abstract concepts (convince, arithmetic) and two concrete concepts (rolling, red) deeply and repeatedly during a concept-scene matching task that grounded each concept in typical contexts. Using a catch trial design, neural activity associated with each concept word was separated from neural activity associated with subsequent visual scenes to assess activations underlying the detailed semantics of each concept. We predicted that brain regions underlying mentalizing and social cognition (e.g., medial prefrontal cortex, superior temporal sulcus) would become active to represent semantic content central to convince, whereas brain regions underlying numerical cognition (e.g., bilateral intraparietal sulcus) would become active to represent semantic content central to arithmetic. The results supported these predictions, suggesting that the meanings of abstract concepts arise from distributed neural systems that represent concept-specific content. PMID:23363408
MEG and fMRI Fusion for Non-Linear Estimation of Neural and BOLD Signal Changes

PubMed Central

Plis, Sergey M.; Calhoun, Vince D.; Weisend, Michael P.; Eichele, Tom; Lane, Terran

2010-01-01

The combined analysis of magnetoencephalography (MEG)/electroencephalography and functional magnetic resonance imaging (fMRI) measurements can lead to improvement in the description of the dynamical and spatial properties of brain activity. In this paper we empirically demonstrate this improvement using simulated and recorded task related MEG and fMRI activity. Neural activity estimates were derived using a dynamic Bayesian network with continuous real valued parameters by means of a sequential Monte Carlo technique. In synthetic data, we show that MEG and fMRI fusion improves estimation of the indirectly observed neural activity and smooths tracking of the blood oxygenation level dependent (BOLD) response. In recordings of task related neural activity the combination of MEG and fMRI produces a result with greater signal-to-noise ratio, that confirms the expectation arising from the nature of the experiment. The highly non-linear model of the BOLD response poses a difficult inference problem for neural activity estimation; computational requirements are also high due to the time and space complexity. We show that joint analysis of the data improves the system's behavior by stabilizing the differential equations system and by requiring fewer computational resources. PMID:21120141
Positive mood enhances reward-related neural activity

PubMed Central

Nusslock, Robin

2016-01-01

Although behavioral research has shown that positive mood leads to desired outcomes in nearly every major life domain, no studies have directly examined the effects of positive mood on the neural processes underlying reward-related affect and goal-directed behavior. To address this gap, participants in the present fMRI study experienced either a positive (n = 20) or neutral (n = 20) mood induction and subsequently completed a monetary incentive delay task that assessed reward and loss processing. Consistent with prediction, positive mood elevated activity specifically during reward anticipation in corticostriatal neural regions that have been implicated in reward processing and goal-directed behavior, including the nucleus accumbens, caudate, lateral orbitofrontal cortex and putamen, as well as related paralimbic regions, including the anterior insula and ventromedial prefrontal cortex. These effects were not observed during reward outcome, loss anticipation or loss outcome. Critically, this is the first study to report that positive mood enhances reward-related neural activity. Our findings have implications for uncovering the neural mechanisms by which positive mood enhances goal-directed behavior, understanding the malleability of reward-related neural activity, and developing targeted treatments for psychiatric disorders characterized by deficits in reward processing. PMID:26833919
Neuralized1 activates CPEB3: a function for nonproteolytic ubiquitin in synaptic plasticity and memory storage.

PubMed

Pavlopoulos, Elias; Trifilieff, Pierre; Chevaleyre, Vivien; Fioriti, Luana; Zairis, Sakellarios; Pagano, Andrew; Malleret, Gaël; Kandel, Eric R

2011-12-09

The cytoplasmic polyadenylation element-binding protein 3 (CPEB3), a regulator of local protein synthesis, is the mouse homolog of ApCPEB, a functional prion protein in Aplysia. Here, we provide evidence that CPEB3 is activated by Neuralized1, an E3 ubiquitin ligase. In hippocampal cultures, CPEB3 activated by Neuralized1-mediated ubiquitination leads both to the growth of new dendritic spines and to an increase of the GluA1 and GluA2 subunits of AMPA receptors, two CPEB3 targets essential for synaptic plasticity. Conditional overexpression of Neuralized1 similarly increases GluA1 and GluA2 and the number of spines and functional synapses in the hippocampus and is reflected in enhanced hippocampal-dependent memory and synaptic plasticity. By contrast, inhibition of Neuralized1 reduces GluA1 and GluA2 levels and impairs hippocampal-dependent memory and synaptic plasticity. These results suggest a model whereby Neuralized1-dependent ubiquitination facilitates hippocampal plasticity and hippocampal-dependent memory storage by modulating the activity of CPEB3 and CPEB3-dependent protein synthesis and synapse formation. Copyright © 2011 Elsevier Inc. All rights reserved.
Lag Synchronization of Switched Neural Networks via Neural Activation Function and Applications in Image Encryption.

PubMed

Wen, Shiping; Zeng, Zhigang; Huang, Tingwen; Meng, Qinggang; Yao, Wei

2015-07-01

This paper investigates the problem of global exponential lag synchronization of a class of switched neural networks with time-varying delays via neural activation function and applications in image encryption. The controller is dependent on the output of the system in the case of packed circuits, since it is hard to measure the inner state of the circuits. Thus, it is critical to design the controller based on the neuron activation function. Comparing the results, in this paper, with the existing ones shows that we improve and generalize the results derived in the previous literature. Several examples are also given to illustrate the effectiveness and potential applications in image encryption.
Robotic Planetary Drill Tests

NASA Technical Reports Server (NTRS)

Glass, Brian J.; Thompson, S.; Paulsen, G.

2010-01-01

Several proposed or planned planetary science missions to Mars and other Solar System bodies over the next decade require subsurface access by drilling. This paper discusses the problems of remote robotic drilling, an automation and control architecture based loosely on observed human behaviors in drilling on Earth, and an overview of robotic drilling field test results using this architecture since 2005. Both rotary-drag and rotary-percussive drills are targeted. A hybrid diagnostic approach incorporates heuristics, model-based reasoning and vibration monitoring with neural nets. Ongoing work leads to flight-ready drilling software.
Neural Correlates of Belief- and Desire-Reasoning in 7- and 8-year-old Children: An Event-Related Potential Study

PubMed Central

Bowman, Lindsay C.; Liu, David; Meltzoff, Andrew N.; Wellman, Henry M.

2012-01-01

Theory of mind requires belief- and desire-understanding. Event-related brain potential (ERP) research on belief- and desire-reasoning in adults found mid-frontal activations for both desires and beliefs, and selective right-posterior activations only for beliefs. Developmentally, children understand desires before beliefs; thus, a critical question concerns whether neural specialization for belief-reasoning exists in childhood or develops later. Neural activity was recorded as 7- and 8-year-olds (N = 18) performed the same diverse-desires, diverse-beliefs, and physical control tasks used in a previous adult ERP study. Like adults, mid-frontal scalp activations were found for belief- and desire-reasoning. Moreover, analyses using correct trials alone yielded selective right-posterior activations for belief-reasoning. Results suggest developmental links between increasingly accurate understanding of complex mental states and neural specialization supporting this understanding. PMID:22925510
New results for global exponential synchronization in neural networks via functional differential inclusions.

PubMed

Wang, Dongshu; Huang, Lihong; Tang, Longkun

2015-08-01

This paper is concerned with the synchronization dynamical behaviors for a class of delayed neural networks with discontinuous neuron activations. Continuous and discontinuous state feedback controller are designed such that the neural networks model can realize exponential complete synchronization in view of functional differential inclusions theory, Lyapunov functional method and inequality technique. The new proposed results here are very easy to verify and also applicable to neural networks with continuous activations. Finally, some numerical examples show the applicability and effectiveness of our main results.
Dispositional Mindfulness and Depressive Symptomatology: Correlations with Limbic and Self-Referential Neural Activity during Rest

PubMed Central

Way, Baldwin M.; Creswell, J. David; Eisenberger, Naomi I.; Lieberman, Matthew D.

2010-01-01

To better understand the relationship between mindfulness and depression, we studied normal young adults (n=27) who completed measures of dispositional mindfulness and depressive symptomatology, which were then correlated with: a) Rest: resting neural activity during passive viewing of a fixation cross, relative to a simple goal-directed task (shape-matching); and b) Reactivity: neural reactivity during viewing of negative emotional faces, relative to the same shape-matching task. Dispositional mindfulness was negatively correlated with resting activity in self-referential processing areas, while depressive symptomatology was positively correlated with resting activity in similar areas. In addition, dispositional mindfulness was negatively correlated with resting activity in the amygdala, bilaterally, while depressive symptomatology was positively correlated with activity in the right amygdala. Similarly, when viewing emotional faces, amygdala reactivity was positively correlated with depressive symptomatology and negatively correlated with dispositional mindfulness, an effect that was largely attributable to differences in resting activity. These findings indicate that mindfulness is associated with intrinsic neural activity and that changes in resting amygdala activity could be a potential mechanism by which mindfulness-based depression treatments elicit therapeutic improvement. PMID:20141298
Phase synchronization motion and neural coding in dynamic transmission of neural information.

PubMed

Wang, Rubin; Zhang, Zhikang; Qu, Jingyi; Cao, Jianting

2011-07-01

In order to explore the dynamic characteristics of neural coding in the transmission of neural information in the brain, a model of neural network consisting of three neuronal populations is proposed in this paper using the theory of stochastic phase dynamics. Based on the model established, the neural phase synchronization motion and neural coding under spontaneous activity and stimulation are examined, for the case of varying network structure. Our analysis shows that, under the condition of spontaneous activity, the characteristics of phase neural coding are unrelated to the number of neurons participated in neural firing within the neuronal populations. The result of numerical simulation supports the existence of sparse coding within the brain, and verifies the crucial importance of the magnitudes of the coupling coefficients in neural information processing as well as the completely different information processing capability of neural information transmission in both serial and parallel couplings. The result also testifies that under external stimulation, the bigger the number of neurons in a neuronal population, the more the stimulation influences the phase synchronization motion and neural coding evolution in other neuronal populations. We verify numerically the experimental result in neurobiology that the reduction of the coupling coefficient between neuronal populations implies the enhancement of lateral inhibition function in neural networks, with the enhancement equivalent to depressing neuronal excitability threshold. Thus, the neuronal populations tend to have a stronger reaction under the same stimulation, and more neurons get excited, leading to more neurons participating in neural coding and phase synchronization motion.
Global Neural Pattern Similarity as a Common Basis for Categorization and Recognition Memory

PubMed Central

Xue, Gui; Love, Bradley C.; Preston, Alison R.; Poldrack, Russell A.

2014-01-01

Familiarity, or memory strength, is a central construct in models of cognition. In previous categorization and long-term memory research, correlations have been found between psychological measures of memory strength and activation in the medial temporal lobes (MTLs), which suggests a common neural locus for memory strength. However, activation alone is insufficient for determining whether the same mechanisms underlie neural function across domains. Guided by mathematical models of categorization and long-term memory, we develop a theory and a method to test whether memory strength arises from the global similarity among neural representations. In human subjects, we find significant correlations between global similarity among activation patterns in the MTLs and both subsequent memory confidence in a recognition memory task and model-based measures of memory strength in a category learning task. Our work bridges formal cognitive theories and neuroscientific models by illustrating that the same global similarity computations underlie processing in multiple cognitive domains. Moreover, by establishing a link between neural similarity and psychological memory strength, our findings suggest that there may be an isomorphism between psychological and neural representational spaces that can be exploited to test cognitive theories at both the neural and behavioral levels. PMID:24872552
Bottom-up driven involuntary auditory evoked field change: constant sound sequencing amplifies but does not sharpen neural activity.

PubMed

Okamoto, Hidehiko; Stracke, Henning; Lagemann, Lothar; Pantev, Christo

2010-01-01

The capability of involuntarily tracking certain sound signals during the simultaneous presence of noise is essential in human daily life. Previous studies have demonstrated that top-down auditory focused attention can enhance excitatory and inhibitory neural activity, resulting in sharpening of frequency tuning of auditory neurons. In the present study, we investigated bottom-up driven involuntary neural processing of sound signals in noisy environments by means of magnetoencephalography. We contrasted two sound signal sequencing conditions: "constant sequencing" versus "random sequencing." Based on a pool of 16 different frequencies, either identical (constant sequencing) or pseudorandomly chosen (random sequencing) test frequencies were presented blockwise together with band-eliminated noises to nonattending subjects. The results demonstrated that the auditory evoked fields elicited in the constant sequencing condition were significantly enhanced compared with the random sequencing condition. However, the enhancement was not significantly different between different band-eliminated noise conditions. Thus the present study confirms that by constant sound signal sequencing under nonattentive listening the neural activity in human auditory cortex can be enhanced, but not sharpened. Our results indicate that bottom-up driven involuntary neural processing may mainly amplify excitatory neural networks, but may not effectively enhance inhibitory neural circuits.
Dysfunctional long-range coordination of neural activity during Gestalt perception in schizophrenia.

PubMed

Uhlhaas, Peter J; Linden, David E J; Singer, Wolf; Haenschel, Corinna; Lindner, Michael; Maurer, Konrad; Rodriguez, Eugenio

2006-08-02

Recent theoretical and empirical research on schizophrenia converges on the notion that core aspects of the pathophysiology of the disorder may arise from a dysfunction in the coordination of distributed neural activity. Synchronization of neural responses in the beta-band (15-30 Hz) and gamma-band range (30-80 Hz) has been implicated as a possible neural substrate for dysfunctional coordination in schizophrenia. To test this hypothesis, we examined the electroencephalography (EEG) activity in 19 patients with a Diagnostic and Statistical Manual of Mental Disorder, edition IV criteria, diagnosis of schizophrenia and 19 healthy control subjects during a Gestalt perception task. EEG data were analyzed for phase synchrony and induced spectral power as an index of neural synchronization. Schizophrenia patients were impaired significantly in the detection of images that required the grouping of stimulus elements into coherent object representations. This deficit was accompanied by longer reaction times in schizophrenia patients. Deficits in Gestalt perception in schizophrenia patients were associated with reduced phase synchrony in the beta-band (20-30 Hz), whereas induced spectral power in the gamma-band (40-70 Hz) was mainly intact. Our findings suggest that schizophrenia patients are impaired in the long-range synchronization of neural responses, which may reflect a core deficit in the coordination of neural activity and underlie the specific cognitive dysfunctions associated with the disorder.

Examining FKBP5 mRNA expression in human iPSC-derived neural cells

PubMed Central

Lieberman, Richard; Kranzler, Henry R.; Levine, Eric S.; Covault, Jonathan

2016-01-01

In peripheral blood leukocytes, FKBP5 mRNA expression is upregulated following glucocorticoid receptor activation. The single nucleotide polymorphism rs1360780 in FKBP5 is associated with psychiatric illness and has functional molecular effects. However, examination of FKBP5 regulation has largely been limited to peripheral cells, which may not reflect regulation in neural cells. We used 27 human induced pluripotent stem cell lines (iPSCs) derived from 20 subjects to examine FKBP5 mRNA expression following GR activation. Following differentiation into forebrain-lineage neural cultures, cells were exposed to 1μM dexamethasone and mRNA expression of FKBP5 and NR3C1 analyzed. Results from the iPSC-derived neural cells were compared with those from 15 donor matched fibroblast lines. Following dexamethasone treatment, there was a 670% increase in FKBP5 expression in fibroblasts, mimicking findings in peripheral blood-derived cells, but only a 23% increase in iPSC-derived neural cultures. FKBP5 rs1360780 genotype did not affect the induction of FKBP5 mRNA in either fibroblasts or neural cells. These results suggest that iPSC-derived forebrain-lineage neurons may not be an optimal neural cell type in which to examine relationships between GR activation, FKBP5 expression, and genetic variation in human subjects. Further, FKBP5 induction following GR activation may differ between cell types derived from the same individual. PMID:27915167
Analysis of electromyographic activity in spastic biceps brachii muscle following neural mobilization.

PubMed

Castilho, Jéssica; Ferreira, Luiz Alfredo Braun; Pereira, Wagner Menna; Neto, Hugo Pasini; Morelli, José Geraldo da Silva; Brandalize, Danielle; Kerppers, Ivo Ilvan; Oliveira, Claudia Santos

2012-07-01

Hypertonia is prevalent in anti-gravity muscles, such as the biceps brachii. Neural mobilization is one of the techniques currently used to reduce spasticity. The aim of the present study was to assess electromyographic (EMG) activity in spastic biceps brachii muscles before and after neural mobilization of the upper limb contralateral to the hemiplegia. Repeated pre-test and post-test EMG measurements were performed on six stroke victims with grade 1 or 2 spasticity (Modified Ashworth Scale). The Upper Limb Neurodynamic Test (ULNT1) was the mobilization technique employed. After neural mobilization contralateral to the lesion, electromyographic activity in the biceps brachii decreased by 17% and 11% for 90° flexion and complete extension of the elbow, respectively. However, the results were not statistically significant (p gt; 0.05). When performed using contralateral techniques, neural mobilization alters the electrical signal of spastic muscles. Copyright © 2011 Elsevier Ltd. All rights reserved.
Neural differences between intrinsic reasons for doing versus extrinsic reasons for doing: an fMRI study.

PubMed

Lee, Woogul; Reeve, Johnmarshall; Xue, Yiqun; Xiong, Jinhu

2012-05-01

The contemporary neural understanding of motivation is based almost exclusively on the neural mechanisms of incentive motivation. Recognizing this as a limitation, we used event-related functional magnetic resonance imaging (fMRI) to pursue the viability of expanding the neural understanding of motivation by initiating a pioneering study of intrinsic motivation by scanning participants' neural activity when they decided to act for intrinsic reasons versus when they decided to act for extrinsic reasons. As expected, intrinsic reasons for acting more recruited insular cortex activity while extrinsic reasons for acting more recruited posterior cingulate cortex (PCC) activity. The results demonstrate that engagement decisions based on intrinsic motivation are more determined by weighing the presence of spontaneous self-satisfactions such as interest and enjoyment while engagement decisions based on extrinsic motivation are more determined by weighing socially-acquired stored values as to whether the environmental incentive is attractive enough to warrant action.
QSAR modelling using combined simple competitive learning networks and RBF neural networks.

PubMed

Sheikhpour, R; Sarram, M A; Rezaeian, M; Sheikhpour, E

2018-04-01

The aim of this study was to propose a QSAR modelling approach based on the combination of simple competitive learning (SCL) networks with radial basis function (RBF) neural networks for predicting the biological activity of chemical compounds. The proposed QSAR method consisted of two phases. In the first phase, an SCL network was applied to determine the centres of an RBF neural network. In the second phase, the RBF neural network was used to predict the biological activity of various phenols and Rho kinase (ROCK) inhibitors. The predictive ability of the proposed QSAR models was evaluated and compared with other QSAR models using external validation. The results of this study showed that the proposed QSAR modelling approach leads to better performances than other models in predicting the biological activity of chemical compounds. This indicated the efficiency of simple competitive learning networks in determining the centres of RBF neural networks.
Neural Pathways of Embarrassment and their Modulation by Social Anxiety

PubMed Central

Müller-Pinzler, L; Gazzola, V; Keysers, C; Sommer, J; Jansen, A; Frässle, S; Einhäuser, W

2016-01-01

While being in the center of attention and exposed to other’s evaluations humans are prone to experience embarrassment. To characterize the neural underpinnings of such aversive moments, we induced genuine experiences of embarrassment during person-group interactions in a functional neuroimaging study. Using a mock-up scenario with three confederates, we examined how the presence of an audience affected physiological and neural responses and the reported emotional experiences of failures and achievements. The results indicated that publicity induced activations in mentalizing areas and failures led to activations in arousal processing systems. Mentalizing activity as well as attention towards the audience were increased in socially anxious participants. The converging integration of information from mentalizing areas and arousal processing systems within the ventral anterior insula and amygdala form the neural pathways of embarrassment. Targeting these neural markers of embarrassment in the (para-)limbic system provides new perspectives for developing treatment strategies for social anxiety disorders. PMID:26093329
Preconditioning electromyographic data for an upper extremity model using neural networks

NASA Technical Reports Server (NTRS)

Roberson, D. J.; Fernjallah, M.; Barr, R. E.; Gonzalez, R. V.

1994-01-01

A back propagation neural network has been employed to precondition the electromyographic signal (EMG) that drives a computational model of the human upper extremity. This model is used to determine the complex relationship between EMG and muscle activation, and generates an optimal muscle activation scheme that simulates the actual activation. While the experimental and model predicted results of the ballistic muscle movement are very similar, the activation function between the start and the finish is not. This neural network preconditions the signal in an attempt to more closely model the actual activation function over the entire course of the muscle movement.
Risky Decision Making in Neurofibromatosis Type 1: An Exploratory Study

PubMed Central

Jonas, Rachel K.; Roh, EunJi; Montojo, Caroline A.; Pacheco, Laura A.; Rosser, Tena; Silva, Alcino J.; Bearden, Carrie E.

2016-01-01

Background Neurofibromatosis type 1 (NF1) is a monogenic disorder affecting cognitive function. About one third of children with NF1 have attentional disorders, and the cognitive phenotype is characterized by impairment in prefrontally-mediated functions. Mouse models of NF1 show irregularities in GABA release and striatal dopamine metabolism. We hypothesized that youth with NF1 would show abnormal behavior and neural activity on a task of risk-taking reliant on prefrontal-striatal circuits. Methods Youth with NF1 (N=29) and demographically comparable healthy controls (N=22), ages 8-19, were administered a developmentally sensitive gambling task, in which they chose between low-risk gambles with a high probability of obtaining a small reward, and high-risk gambles with a low probability of obtaining a large reward. We used functional magnetic resonance imaging (fMRI) to investigate neural activity associated with risky decision making, as well as age-associated changes in these behavioral and neural processes. Results Behaviorally, youth with NF1 tended to make fewer risky decisions than controls. Neuroimaging analyses revealed significantly reduced neural activity across multiple brain regions involved in higher-order semantic processing and motivation (i.e., anterior cingulate, paracingulate, supramarginal, and angular gyri) in patients with NF1 relative to controls during the task. We also observed atypical age-associated changes in neural activity in patients with NF1, such that during risk taking, neural activity tended to decrease with age in controls, whereas it tended to increase with age in patients with NF1. Conclusions Findings suggest that developmental trajectories of neural activity during risky decision-making may be disrupted in youth with NF1. PMID:28736755
12-Deoxyphorbols Promote Adult Neurogenesis by Inducing Neural Progenitor Cell Proliferation via PKC Activation

PubMed Central

Geribaldi-Doldán, Noelia; Flores-Giubi, Eugenia; Murillo-Carretero, Maribel; García-Bernal, Francisco; Carrasco, Manuel; Macías-Sánchez, Antonio J.; Domínguez-Riscart, Jesús; Verástegui, Cristina; Hernández-Galán, Rosario

2016-01-01

Background: Neuropsychiatric and neurological disorders frequently occur after brain insults associated with neuronal loss. Strategies aimed to facilitate neuronal renewal by promoting neurogenesis constitute a promising therapeutic option to treat neuronal death-associated disorders. In the adult brain, generation of new neurons occurs physiologically throughout the entire life controlled by extracellular molecules coupled to intracellular signaling cascades. Proteins participating in these cascades within neurogenic regions constitute potential pharmacological targets to promote neuronal regeneration of injured areas of the central nervous system. Methodology: We have performed in vitro and in vivo approaches to determine neural progenitor cell proliferation to understand whether activation of kinases of the protein kinase C family facilitates neurogenesis in the adult brain. Results: We have demonstrated that protein kinase C activation by phorbol-12-myristate-13-acetate induces neural progenitor cell proliferation in vitro. We also show that the nontumorogenic protein kinase C activator prostratin exerts a proliferative effect on neural progenitor cells in vitro. This effect can be reverted by addition of the protein kinase C inhibitor G06850, demonstrating that the effect of prostratin is mediated by protein kinase C activation. Additionally, we show that prostratin treatment in vivo induces proliferation of neural progenitor cells within the dentate gyrus of the hippocampus and the subventricular zone. Finally, we describe a library of diterpenes with a 12-deoxyphorbol structure similar to that of prostratin that induces a stronger effect than prostratin on neural progenitor cell proliferation both in vitro and in vivo. Conclusions: This work suggests that protein kinase C activation is a promising strategy to expand the endogenous neural progenitor cell population to promote neurogenesis and highlights the potential of 12-deoxyphorbols as pharmaceutical agents to facilitate neuronal renewal. PMID:26224011
12-Deoxyphorbols Promote Adult Neurogenesis by Inducing Neural Progenitor Cell Proliferation via PKC Activation.

PubMed

Geribaldi-Doldán, Noelia; Flores-Giubi, Eugenia; Murillo-Carretero, Maribel; García-Bernal, Francisco; Carrasco, Manuel; Macías-Sánchez, Antonio J; Domínguez-Riscart, Jesús; Verástegui, Cristina; Hernández-Galán, Rosario; Castro, Carmen

2015-07-29

Neuropsychiatric and neurological disorders frequently occur after brain insults associated with neuronal loss. Strategies aimed to facilitate neuronal renewal by promoting neurogenesis constitute a promising therapeutic option to treat neuronal death-associated disorders. In the adult brain, generation of new neurons occurs physiologically throughout the entire life controlled by extracellular molecules coupled to intracellular signaling cascades. Proteins participating in these cascades within neurogenic regions constitute potential pharmacological targets to promote neuronal regeneration of injured areas of the central nervous system. We have performed in vitro and in vivo approaches to determine neural progenitor cell proliferation to understand whether activation of kinases of the protein kinase C family facilitates neurogenesis in the adult brain. We have demonstrated that protein kinase C activation by phorbol-12-myristate-13-acetate induces neural progenitor cell proliferation in vitro. We also show that the nontumorogenic protein kinase C activator prostratin exerts a proliferative effect on neural progenitor cells in vitro. This effect can be reverted by addition of the protein kinase C inhibitor G06850, demonstrating that the effect of prostratin is mediated by protein kinase C activation. Additionally, we show that prostratin treatment in vivo induces proliferation of neural progenitor cells within the dentate gyrus of the hippocampus and the subventricular zone. Finally, we describe a library of diterpenes with a 12-deoxyphorbol structure similar to that of prostratin that induces a stronger effect than prostratin on neural progenitor cell proliferation both in vitro and in vivo. This work suggests that protein kinase C activation is a promising strategy to expand the endogenous neural progenitor cell population to promote neurogenesis and highlights the potential of 12-deoxyphorbols as pharmaceutical agents to facilitate neuronal renewal. © The Author 2015. Published by Oxford University Press on behalf of CINP.
The Affective Impact of Financial Skewness on Neural Activity and Choice

PubMed Central

Wu, Charlene C.; Bossaerts, Peter; Knutson, Brian

2011-01-01

Few finance theories consider the influence of “skewness” (or large and asymmetric but unlikely outcomes) on financial choice. We investigated the impact of skewed gambles on subjects' neural activity, self-reported affective responses, and subsequent preferences using functional magnetic resonance imaging (FMRI). Neurally, skewed gambles elicited more anterior insula activation than symmetric gambles equated for expected value and variance, and positively skewed gambles also specifically elicited more nucleus accumbens (NAcc) activation than negatively skewed gambles. Affectively, positively skewed gambles elicited more positive arousal and negatively skewed gambles elicited more negative arousal than symmetric gambles equated for expected value and variance. Subjects also preferred positively skewed gambles more, but negatively skewed gambles less than symmetric gambles of equal expected value. Individual differences in both NAcc activity and positive arousal predicted preferences for positively skewed gambles. These findings support an anticipatory affect account in which statistical properties of gambles—including skewness—can influence neural activity, affective responses, and ultimately, choice. PMID:21347239
Neural circuits. Labeling of active neural circuits in vivo with designed calcium integrators.

PubMed

Fosque, Benjamin F; Sun, Yi; Dana, Hod; Yang, Chao-Tsung; Ohyama, Tomoko; Tadross, Michael R; Patel, Ronak; Zlatic, Marta; Kim, Douglas S; Ahrens, Misha B; Jayaraman, Vivek; Looger, Loren L; Schreiter, Eric R

2015-02-13

The identification of active neurons and circuits in vivo is a fundamental challenge in understanding the neural basis of behavior. Genetically encoded calcium (Ca(2+)) indicators (GECIs) enable quantitative monitoring of cellular-resolution activity during behavior. However, such indicators require online monitoring within a limited field of view. Alternatively, post hoc staining of immediate early genes (IEGs) indicates highly active cells within the entire brain, albeit with poor temporal resolution. We designed a fluorescent sensor, CaMPARI, that combines the genetic targetability and quantitative link to neural activity of GECIs with the permanent, large-scale labeling of IEGs, allowing a temporally precise "activity snapshot" of a large tissue volume. CaMPARI undergoes efficient and irreversible green-to-red conversion only when elevated intracellular Ca(2+) and experimenter-controlled illumination coincide. We demonstrate the utility of CaMPARI in freely moving larvae of zebrafish and flies, and in head-fixed mice and adult flies. Copyright © 2015, American Association for the Advancement of Science.
Dynamic and Differential Regulation of Stem Cell Factor FoxD3 in the Neural Crest Is Encrypted in the Genome

PubMed Central

Tan-Cabugao, Joanne; Sauka-Spengler, Tatjana; Bronner, Marianne E.

2012-01-01

The critical stem cell transcription factor FoxD3 is expressed by the premigratory and migrating neural crest, an embryonic stem cell population that forms diverse derivatives. Despite its important role in development and stem cell biology, little is known about what mediates FoxD3 activity in these cells. We have uncovered two FoxD3 enhancers, NC1 and NC2, that drive reporter expression in spatially and temporally distinct manners. Whereas NC1 activity recapitulates initial FoxD3 expression in the cranial neural crest, NC2 activity recapitulates initial FoxD3 expression at vagal/trunk levels while appearing only later in migrating cranial crest. Detailed mutational analysis, in vivo chromatin immunoprecipitation, and morpholino knock-downs reveal that transcription factors Pax7 and Msx1/2 cooperate with the neural crest specifier gene, Ets1, to bind to the cranial NC1 regulatory element. However, at vagal/trunk levels, they function together with the neural plate border gene, Zic1, which directly binds to the NC2 enhancer. These results reveal dynamic and differential regulation of FoxD3 in distinct neural crest subpopulations, suggesting that heterogeneity is encrypted at the regulatory level. Isolation of neural crest enhancers not only allows establishment of direct regulatory connections underlying neural crest formation, but also provides valuable tools for tissue specific manipulation and investigation of neural crest cell identity in amniotes. PMID:23284303
Anticipatory anxiety disrupts neural valuation during risky choice.

PubMed

Engelmann, Jan B; Meyer, Friederike; Fehr, Ernst; Ruff, Christian C

2015-02-18

Incidental negative emotions unrelated to the current task, such as background anxiety, can strongly influence decisions. This is most evident in psychiatric disorders associated with generalized emotional disturbances. However, the neural mechanisms by which incidental emotions may affect choices remain poorly understood. Here we study the effects of incidental anxiety on human risky decision making, focusing on both behavioral preferences and their underlying neural processes. Although observable choices remained stable across affective contexts with high and low incidental anxiety, we found a clear change in neural valuation signals: during high incidental anxiety, activity in ventromedial prefrontal cortex and ventral striatum showed a marked reduction in (1) neural coding of the expected subjective value (ESV) of risky options, (2) prediction of observed choices, (3) functional coupling with other areas of the valuation system, and (4) baseline activity. At the same time, activity in the anterior insula showed an increase in coding the negative ESV of risky lotteries, and this neural activity predicted whether the risky lotteries would be rejected. This pattern of results suggests that incidental anxiety can shift the focus of neural valuation from possible positive consequences to anticipated negative consequences of choice options. Moreover, our findings show that these changes in neural value coding can occur in the absence of changes in overt behavior. This suggest a possible pathway by which background anxiety may lead to the development of chronic reward desensitization and a maladaptive focus on negative cognitions, as prevalent in affective and anxiety disorders. Copyright © 2015 the authors 0270-6474/15/353085-15$15.00/0.
Music modulation of pain perception and pain-related activity in the brain, brain stem, and spinal cord: a functional magnetic resonance imaging study.

PubMed

Dobek, Christine E; Beynon, Michaela E; Bosma, Rachael L; Stroman, Patrick W

2014-10-01

The oldest known method for relieving pain is music, and yet, to date, the underlying neural mechanisms have not been studied. Here, we investigate these neural mechanisms by applying a well-defined painful stimulus while participants listened to their favorite music or to no music. Neural responses in the brain, brain stem, and spinal cord were mapped with functional magnetic resonance imaging spanning the cortex, brain stem, and spinal cord. Subjective pain ratings were observed to be significantly lower when pain was administered with music than without music. The pain stimulus without music elicited neural activity in brain regions that are consistent with previous studies. Brain regions associated with pleasurable music listening included limbic, frontal, and auditory regions, when comparing music to non-music pain conditions. In addition, regions demonstrated activity indicative of descending pain modulation when contrasting the 2 conditions. These regions include the dorsolateral prefrontal cortex, periaqueductal gray matter, rostral ventromedial medulla, and dorsal gray matter of the spinal cord. This is the first imaging study to characterize the neural response of pain and how pain is mitigated by music, and it provides new insights into the neural mechanism of music-induced analgesia within the central nervous system. This article presents the first investigation of neural processes underlying music analgesia in human participants. Music modulates pain responses in the brain, brain stem, and spinal cord, and neural activity changes are consistent with engagement of the descending analgesia system. Copyright © 2014 American Pain Society. Published by Elsevier Inc. All rights reserved.
The neural basis of financial risk taking.

PubMed

Kuhnen, Camelia M; Knutson, Brian

2005-09-01

Investors systematically deviate from rationality when making financial decisions, yet the mechanisms responsible for these deviations have not been identified. Using event-related fMRI, we examined whether anticipatory neural activity would predict optimal and suboptimal choices in a financial decision-making task. We characterized two types of deviations from the optimal investment strategy of a rational risk-neutral agent as risk-seeking mistakes and risk-aversion mistakes. Nucleus accumbens activation preceded risky choices as well as risk-seeking mistakes, while anterior insula activation preceded riskless choices as well as risk-aversion mistakes. These findings suggest that distinct neural circuits linked to anticipatory affect promote different types of financial choices and indicate that excessive activation of these circuits may lead to investing mistakes. Thus, consideration of anticipatory neural mechanisms may add predictive power to the rational actor model of economic decision making.
Dynamic Organization of Hierarchical Memories

PubMed Central

Kurikawa, Tomoki; Kaneko, Kunihiko

2016-01-01

In the brain, external objects are categorized in a hierarchical way. Although it is widely accepted that objects are represented as static attractors in neural state space, this view does not take account interaction between intrinsic neural dynamics and external input, which is essential to understand how neural system responds to inputs. Indeed, structured spontaneous neural activity without external inputs is known to exist, and its relationship with evoked activities is discussed. Then, how categorical representation is embedded into the spontaneous and evoked activities has to be uncovered. To address this question, we studied bifurcation process with increasing input after hierarchically clustered associative memories are learned. We found a “dynamic categorization”; neural activity without input wanders globally over the state space including all memories. Then with the increase of input strength, diffuse representation of higher category exhibits transitions to focused ones specific to each object. The hierarchy of memories is embedded in the transition probability from one memory to another during the spontaneous dynamics. With increased input strength, neural activity wanders over a narrower state space including a smaller set of memories, showing more specific category or memory corresponding to the applied input. Moreover, such coarse-to-fine transitions are also observed temporally during transient process under constant input, which agrees with experimental findings in the temporal cortex. These results suggest the hierarchy emerging through interaction with an external input underlies hierarchy during transient process, as well as in the spontaneous activity. PMID:27618549
Comparative Studies of Prediction Strategies for Solar X-ray Time Series

NASA Astrophysics Data System (ADS)

Muranushi, T.; Hattori, T.; Jin, Q.; Hishinuma, T.; Tominaga, M.; Nakagawa, K.; Fujiwara, Y.; Nakamura, T.; Sakaue, T.; Takahashi, T.; Seki, D.; Namekata, K.; Tei, A.; Ban, M.; Kawamura, A. D.; Hada-Muranushi, Y.; Asai, A.; Nemoto, S.; Shibata, K.

2016-12-01

Crucial virtues for operational space weather forecast are real-timeforecast ability, forecast precision and customizability to userneeds. The recent development of deep-learning makes it veryattractive to space weather, because (1) it learns gradually incomingdata, (2) it exhibits superior accuracy over conventional algorithmsin many fields, and (3) it makes the customization of the forecasteasier because it accepts raw images.However, the best deep-learning applications are only attainable bycareful human designers that understands both the mechanism of deeplearning and the application field. Therefore, we need to foster youngresearchers to enter the field of machine-learning aided forecast. So,we have held a seminar every Monday with undergraduate and graduatestudents from May to August 2016.We will review the current status of space weather science and theautomated real-time space weather forecast engine UFCORIN. Then, weintroduce the deep-learning space weather forecast environments wehave set up using Python and Chainer on students' laptop computers.We have started from simple image classification neural network, thenimplemented space-weather neural network that predicts future X-rayflux of the Sun based on the past X-ray lightcurve and magnetic fieldline-of-sight images.In order to perform each forecast faster, we have focused on simplelightcurve-to-lightcurve forecast, and performed comparative surveysby changing following parameters: The size and topology of the neural network Batchsize Neural network hyperparameters such as learning rates to optimize the preduction accuracy, and time for prediction.We have found how to design compact, fast but accurate neural networkto perform forecast. Our forecasters can perform predictionexperiment for four-year timespan in a few minutes, and achieveslog-scale errors of the order of 1. Our studies is ongoing, and inour talk we will review our progress till December.
The Effects of Spaceflight and a Spaceflight Analog on Neurocognitive Perfonnance: Extent, Longevity, and Neural Bases

NASA Technical Reports Server (NTRS)

Seidler, R. D.; Mulavara, A. P.; Koppelmans, V.; Erdeniz, B.; Kofman, I. S.; DeDios, Y. E.; Szecsy, D. L.; Riascos-Castaneda, R. F.; Wood, S. J.; Bloomberg, J. J.

2014-01-01

We are conducting ongoing experiments in which we are performing structural and functional magnetic resonance brain imaging to identify the relationships between changes in neurocognitive function and neural structural alterations following a six month International Space Station mission and following 70 days exposure to a spaceflight analog, head down tilt bedrest. Our central hypothesis is that measures of brain structure, function, and network integrity will change from pre to post intervention (spaceflight, bedrest). Moreover, we predict that these changes will correlate with indices of cognitive, sensory, and motor function in a neuroanatomically selective fashion. Our interdisciplinary approach utilizes cutting edge neuroimaging techniques and a broad ranging battery of sensory, motor, and cognitive assessments that will be conducted pre flight, during flight, and post flight to investigate potential neuroplastic and maladaptive brain changes in crewmembers following long-duration spaceflight. Success in this endeavor would 1) result in identification of the underlying neural mechanisms and operational risks of spaceflight-induced changes in behavior, and 2) identify whether a return to normative behavioral function following re-adaptation to Earth's gravitational environment is associated with a restitution of brain structure and function or instead is supported by substitution with compensatory brain processes. With the bedrest study, we will be able to determine the neural and neurocognitive effects of extended duration unloading, reduced sensory inputs, and increased cephalic fluid distribution. This will enable us to parse out the multiple mechanisms contributing to any spaceflight-induced neural structural and behavioral changes that we observe in the flight study. In this presentation I will discuss preliminary results from six participants who have undergone the bed rest protocol. These individuals show decrements in balance and functional mobility, and alterations in brain structure and function, in association with extended bed rest.
Inhibition of NF-kappa B pathway leads to deregulation of epithelial-mesenchymal transition and neural invasion in pancreatic cancer.

PubMed

Nomura, Alice; Majumder, Kaustav; Giri, Bhuwan; Dauer, Patricia; Dudeja, Vikas; Roy, Sabita; Banerjee, Sulagna; Saluja, Ashok K

2016-12-01

NF-κB has an essential role in the initiation and progression of pancreatic cancer and specifically mediates the induction of epithelial-mesenchymal transition and invasiveness. In this study, we demonstrate the importance of activated NF-κB signaling in EMT induction, lymphovascular metastasis, and neural invasion. Modulation of NF-κB activity was accomplished through the specific NF-κB inhibitor (BAY 11-7085), triptolide, and Minnelide treatment, as well as overexpression of IKBα repressor and IKK activator plasmids. In the classical lymphovascular metastatic cascade, inhibition of NF-κB decreased the expression of several EMT transcription factors (SNAI1, SNAI2, and ZEB1) and mesenchymal markers (VIM and CDH2) and decreased in vitro invasion, which was rescued by IKK activation. This was further demonstrated in vivo via BAY 11-7085 treatment in a orthotopic model of pancreatic cancer. In vivo NF-κB inhibition decreased tumor volume; decreased tumor EMT gene expression, while restoring cell-cell junctions; and decreasing overall metastasis. Furthermore, we demonstrate the importance of active NF-κB signaling in neural invasion. Triptolide treatment inhibits Nerve Growth Factor (NGF) mediated, neural-tumor co-culture in vitro invasion, and dorsal root ganglia (DRG) neural outgrowth through a disruption in tumor-neural cross talk. In vivo, Minnelide treatment decreased neurotrophin expression, nerve density, and sciatic nerve invasion. Taken together, this study demonstrates the importance of NF-κB signaling in the progression of pancreatic cancer through the modulation of EMT induction, lymphovascular invasion, and neural invasion.
When Brain Beats Behavior: Neuroforecasting Crowdfunding Outcomes

PubMed Central

Yoon, Carolyn

2017-01-01

Although traditional economic and psychological theories imply that individual choice best scales to aggregate choice, primary components of choice reflected in neural activity may support even more generalizable forecasts. Crowdfunding represents a significant and growing platform for funding new and unique projects, causes, and products. To test whether neural activity could forecast market-level crowdfunding outcomes weeks later, 30 human subjects (14 female) decided whether to fund proposed projects described on an Internet crowdfunding website while undergoing scanning with functional magnetic resonance imaging. Although activity in both the nucleus accumbens (NAcc) and medial prefrontal cortex predicted individual choices to fund on a trial-to-trial basis in the neuroimaging sample, only NAcc activity generalized to forecast market funding outcomes weeks later on the Internet. Behavioral measures from the neuroimaging sample, however, did not forecast market funding outcomes. This pattern of associations was replicated in a second study. These findings demonstrate that a subset of the neural predictors of individual choice can generalize to forecast market-level crowdfunding outcomes—even better than choice itself. SIGNIFICANCE STATEMENT Forecasting aggregate behavior with individual neural data has proven elusive; even when successful, neural forecasts have not historically supplanted behavioral forecasts. In the current research, we find that neural responses can forecast market-level choice and outperform behavioral measures in a novel Internet crowdfunding context. Targeted as well as model-free analyses convergently indicated that nucleus accumbens activity can support aggregate forecasts. Beyond providing initial evidence for neuropsychological processes implicated in crowdfunding choices, these findings highlight the ability of neural features to forecast aggregate choice, which could inform applications relevant to business and policy. PMID:28821681

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