Cognitive neuroscience

Laney, Campbell, Heuer, and Reisberg (2004) proposed that the preferential recall of
central relative to peripheral information in a negative event (known as "memory
narrowing") is the product of presenting participants with a visually arousing attention
magnet -- not negative emotion, as the Easterbrook ( 1959) hypothesis suggests. Laney et
al. used conceptually meaningful (or thematically arousing) events to stimulate an
emotional response in participants instead of visual arousal and found evidence that
negative arousal improves memory for all categories of details. The current study tested
Laney et al. 's theory that a visually arousing stimulus, rather than negative arousal, is
responsible for memory nan·owing as well as their position that negative arousal benefits
recall of both central and peripheral information. Support was found for both assertions
of Laney et al. The presence of a visually salient and emotionally provoking detail
produced an effect similar to the traditional memory narrowing pattem and exposure to
the negative thematic climax resulted in improved memory performance for all the detail
categories. However, this latter effect was observed only for the female participants. No
evidence was found to support the Easterbrook hypothesis.

We sought to better understand human motor control by investigating functional interactions between the Supplementary Motor Area (SMA), dorsal Anterior Cingulate Cortex (dACC), and primary motor cortex (M1) in healthy adolescent participants performing visually coordinated unimanual finger-movement and n-back working memory tasks. We discovered modulation of the SMA by the dACC by analysis of fMRI BOLD time series recorded from the three ROIs (SMA, dACC, and M1) in each participant. Two measures of functional interaction were used: undirected functional connectivity was measured using the Pearson product-moment correlation coefficient (PMCC), and directed functional connectivity was measured from linear autoregressive (AR) models. In the first project, task-specific modulation of the SMA by the dACC was discovered while subjects performed a coordinated unimanual finger-movement task, in which the finger movement was synchronized with an exogenous visual stimulus. In the second project, modulation of the SMA by the dACC was found to be significantly greater in the finger coordination task than in an n-back working memory, in which the same finger movement signified a motor response indicating a 0-back or 2-back working memory match. We thus demonstrated in the first study that the dACC sends task-specific directed signals to the supplementary motor area, suggesting a role for the dACC in top-down motor control. Finally, the second study revealed that these signals were significantly greater in the coordinated motor task than in the n-back working memory task, suggesting that the modulation of the SMA by the dACC was associated with sustained, continuous motor production and/or motor expectation, rather than with the motor movement itself.

SK channels are small conductance Ca2+-activated K+ channels expressed throughout the CNS. SK channels modulate the excitability of hippocampal CA1 neurons by affecting afterhyperpolarization and shaping excitatory postsynaptic responses. Such SK-mediated effects on activity-dependent neuronal excitability and synaptic strength are thought to underlie the modulatory influence of SK channels on memory encoding. Here,the effect of a new SK1 selective activator, GW542573X, on hippocampal-dependent object memory, contextual and cued conditioning, and trace fear conditioning was examined. The results demonstrated that pre- but not post-training systemic administration of GW542573X impaired object memory and trace fear memory in mice 24 h after training. Contextual and cued fear memory were not disrupted. These current data suggest that activation of SK1 subtype-containing SK channels impairs long-term memory. These results are consistent with converging evidence that SK channel activation suppressed behaviorally triggered synaptic plasticity necessary for encoding hippocampal-dependent memory.

Neuronal cell adhesion molecules of L1 family play a critical role in proper nervous system development. Various mutations on human L1-CAM that lead to severe
neurodevelopmental disorders like retardation, spasticity etc. termed under L1 syndrome. The vertebrr their roles in axon pathfinding, neurite extension and cell migration, howeverate L1CAM and its homolog in Drosophila, neuroglian (nrg) have been well studied fo, much less is known about the mechanisms by which they fine tune synaptic connectivity to control the development and maintenance of synaptic connections within neuronal circuits. Here we characterized the essential role of nrg in regulating synaptic structure and function in vivo in a well characterized Drosophila central synapse model neuron, the Giant Fiber (GF) system. Previous studies from our lab revealed that the phosphorylation status of the tyrosine in the Ankyrin binding FIGQY motif in the intracellular domain of Nrg iscrucial for synapse formation of the GF to Tergo-Trochanteral Motor neuron (TTMn) synapse in the GF circuit.
The present work provided us with novel insights into the role of Nrg-Ank interaction in regulating Nrg function during synapse formation and maintenance. By
utilizing a sophisticated Pacman based genomic rescue strategy we have shown that
dynamic regulation of the Neuroglian–Ankyrin interaction is required to coordinate
transsynaptic development in the GF–TTMn synapse. In contrast, the strength of Ankyrin binding directly controls the balance between synapse formation and maintenance at the NMJ.
Human L1 pathological mutations affect different biological processes distinctively
and thus their proper characterization in vivo is essential to understand L1CAM function.
By utilizing nrg14;P[nrg180ΔFIGQY] mutants that have exclusive synaptic defects and the previously characterized nrg849 allele that affected both GF guidance and synaptic function, we were able to analyze pathological L1CAM missense mutations with respect to their effects on guidance and synapse formation in vivo. We found that the human pathological H210Q, R184Q and Y1070C, but not the E309K and L120V L1CAM mutations affect outside-in signaling via the FIGQY Ankyrin binding domain which is required for synapse formation and not for axon guidance while L1CAM homophilic binding and signaling via the ERM motif is essential for axon guidance in Drosophila.

Bering and colleagues (2004, 2005) reported that the expectation that conscious
mental states cease with the onset of death (discontinuity reasoning) emerges
developmentally, and discontinuity reasoning for some states (emotions, desire,
epistemic) remains lower than for others (psychobiological, perceptual). Cormier (2005)
reported very similar findings for the context of sleep and proposed a modular
explanation of these effects (“intentional persistence”) and suggested that intentional
persistence represents an evolved adaptation designed to maintain vigilance and
behavioral preparedness while in the presence of animals of ambiguous agency status
(e.g., death, sleep, hibernation, feigned death). The current study extended this line of
research to realistic animal characters. Although results revealed patterns of discontinuity
reasoning and intentional persistence that were consistent with those of previous studies,
the prediction that intentional persistence would be more pronounced for predators was not fulfilled. A newly proposed evolutionary product, “Cooptation,” was introduced to
further explain the results.

Autism is a neurodevelopmental disorder that is characterized by deficits
involving social interaction, communication, and perception. Although there is much
research that has examined functional neural connectivity in individuals with autism, few
have conducted these studies in very young children while awake across EEG power and coherence measures. Anomalies in EEG coherence and power have been associated with deficits in executive function and mental activity. The present study examined neural activation and functional connectivity with an EEG, in children ages 3 -5, during an eyesclosed baseline period. Discrete Fourier Transform was performed on artifact-free segments of EEG data to produce power density values. In addition, coherence measurements were examined to assess functional connectivity in the alpha bandwidth during the baseline recording. Children with autism spectrum disorder (ASD)
demonstrated reduced alpha coherence in fronto-temporal regions and between right
temporal sites when compared to typically developing (TD) children. In addition, the reduction in coherence was based on ASD severity, such that high-functioning children
with ASD showed greater coherence than low-functioning children with ASD. Children
with ASD also displayed reduced power in the alpha, beta, and theta frequency
bandwidths in frontal, temporal, central, and occipital regions compared to TD children.
Interestingly, delta power differentiated children based on developmental status such that high-functioning children with ASD demonstrated the greatest delta power, followed by TD children, and then low-functioning children with ASD. Finally, TD children
demonstrated left anterior temporal EEG asymmetry in the alpha bandwidth, whereas
children with high-functioning ASD exhibited left posterior temporal EEG asymmetry
and right frontal EEG asymmetry. Thus, the results suggest that children with ASD
exhibit atypical patterns of brain activity and functional connectivity compared to their
typically developing counterparts.

The dynamics of human sensorimotor coordination are studied at behavioral and neural levels through temporal synchronization and syncopation tasks. In experiment 1, subjects synchronized their finger movements (in-phase) with a metronome at 2.0Hz and 1.25Hz for 1200 cycles. Fluctuations of timing errors were analyzed through correlation, power spectrum analyses and Maximum Likelihood Estimation (MLE). Results indicated that the synchronization error time series was characterized by a 1/falpha type of long memory process with alpha = 0.5. Previous timing models based upon motor program or simple "central clock" ideas were reviewed to show that they could not explain such long range correlations in the synchronization task. To explore the possible cognitive origins of long range correlation, experiment 2 required subjects to synchronize (on the beat) or syncopate (off the beat) to a metronome at 1Hz using different cognitive strategies. Timing fluctuations were again found to be 1/f alpha type, with alpha = 0.5 in synchronization and alpha = 0.8 in syncopation. When subjects employed a synchronization strategy to successfully syncopate, timing fluctuations shifted toward 1/f 0.5 type. This experiment indicated that the scaling exponent in timing fluctuations was related to task requirements and specific coordination strategies. Further, they suggest that the sources of such long memory originated from higher level cognitive processing in the human brain. Experiment 3 analyzed magnetoencephalography (MEG) data associated with synchronization and syncopation tasks. Brain oscillations at alpha (8--14Hz), beta (15--20Hz) and gamma (35--40Hz) frequency ranges were shown to correlate with different aspects of the coordination behavior. Specifically, through power and coherence analyses, alpha activity was linked to sensorimotor integration and "binding", beta activity was related to task requirements (synchronization or syncopation), and gamma activity was related to movement kinematics (trajectory). These results supported the idea that the 1/f alpha type of timing fluctuations originated from collective neural activities in the brain acting on multiple time scales.

Experimental and computational investigations addressing how various neural functions are achieved in the brain converged in recent years to a unified idea that the neural activity underlying most of the cognitive functions is distributed over large scale networks comprising various cortical and subcortical areas. Modeling approaches represent these areas and their connections using diverse models of neurocomputational units engaged in graph-like or neural field-like structures. Regardless of the manner of network implementation, simulations of large scale networks have encountered significant difficulties mainly due to the time delay introduced by the long range connections. To decrease the computational effort, it is common to assume severe approximations to simplify the descriptions of the neural dynamics associated with the system's units. In this dissertation we propose an alternative framework allowing the prevention of such strong assumptions while efficiently representing th e dynamics of a complex neural network. First, we consider the dynamics of small scale networks of globally coupled non-identical excitatory and inhibitory neurons, which could realistically instantiate a neurocomputational unit. We identify the most significant dynamical features the neural population exhibits in different parametric configuration, including multi-cluster dynamics, multi-scale synchronization and oscillator death. Then, using mode decomposition techniques, we construct analytically low dimensional representations of the network dynamics and show that these reduced systems capture the dynamical features of the entire neural population. The cases of linear and synaptic coupling are discussed in detail. In chapter 5, we extend this approach for spatially extended neural networks.

It is well established that anticipation of the arrival of an expected stimulus is accompanied by rich ongoing oscillatory neurodynamics, which span and link large areas of cortex. An intriguing possibility is that these dynamic interactions may convey knowledge that is embodied by large-scale neurocognitive networks from higher level regions of multi-model cortex to lower level primary sensory areas. In the current study, using autoregressive spectral analysis, we establish that during the anticipatory phase of a visual discrimination task there are rich patterns of coherent interaction between various levels of the ventral visual hierarchy across the frequency spectrum of 8 - 90 Hz. Using spectral Granger causality we determined that a subset of these interactions carry beta frequency (14 - 30 Hz) top-down influences from higher level visual regions V4 and TEO to primary visual cortex. We investigated the functional significance of these top-down interactions by correlating the magnitude of the anticipatory signals with the amplitude of the visual evoked potential that was elicited by stimulus processing. We found that in one third of the extrastriate-striate pairs, tested in three monkeys, the amplitude of the visual evoked response is well predicted by the magnitude of pre-stimulus coherent top-down anticipatory influences. To investigate the dynamics of the coherent and topdown Granger causal interactions, we analyzed the relationship between coherence and top-down Granger causality with stimulus onset asynchrony. This analysis revealed that in an abundance of cases the magnitudes of the coherent interactions and top-down directional influences scaled with the length of time that had elapsed before stimulus onset.

This study investigated electroencephalographic differences related to cue (central left- or right-directed arrows) in a covert endogenous visual spatial attention task patterned after that of Hopf and Mangun (2000). This was done with the intent of defining the timing of components in relation to cognitive processes within the cue-target interval. Multiple techniques were employed to do this. Event-related potentials (ERPs) were examined using Independent Component Analysis. This revealed a significant N1, between 100:200 ms post-cue, greater contralateral to the cue. Difference wave ERPs, left minus right cue-locked data, divulged significant early directing attention negativity (EDAN) at 200:400 ms post-cue in the right posterior which reversed polarity in the left posterior. Temporal spectral evolution (TSE) analysis of the alpha band revealed three stages, (1) high bilateral alpha precue to 120 ms post-cue, (2) an event related desynchronization (ERD) from approximately 120 ms: 500 ms post-cue, and (3) an event related synchronization (ERS) rebound, 500: 900 ms post-cue, where alpha amplitude, a measure of activity, was highest contralateral to the ignored hemifield and lower contralateral to the attended hemifield. Using a combination of all of these components and scientific literature in this field, it is possible to plot out the time course of the cognitive events and their neural correlates.