Synaptic compensation on Hopfield network: implications for memory rehabilitation

The discrete-time neural network proposed by Hopfield can be used for storing and recognizing binary patterns. Here, we investigate how the performance of this network on pattern recognition task is altered when neurons are removed and the weights of the synapses corresponding to these deleted neurons are divided among the remaining synapses. Five distinct ways of distributing such weights are evaluated. We speculate how this numerical work about synaptic compensation may help to guide experimental studies on memory rehabilitation interventions.

Long-term potentiation of synaptic transmission in the avian hippocampus

The avian hippocampus plays a pivotal role in memory required for spatial navigation and food storing. Here we have examined synaptic transmission and plasticity within the hippocampal formation of the domestic chicken using an in vitro slice preparation. With the use of sharp microelectrodes we have shown that excitatory synaptic inputs in this structure are glutamatergic and activate both NMDA-and AMPA-type receptors on the postsynaptic membrane. In response to tetanic stimulation, the EPSP displayed a robust long-term potentiation (LTP) lasting >1 hr. This LTP was unaffected by blockade of NMDA receptors or chelation of postsynaptic calcium. Application of forskolin increased the EPSP and reduced paired-pulse facilitation: (PPF), indicating an increase in release probability. In contrast, LTP was not associated with a change in the PPF ratio. Induction of LTP did not occlude the effects of forskolin. Thus, in contrast to NMDA receptor-independent LTP in the mammalian brain, LTP in the chicken hippocampus is not attributable to a change in the probability of transmitter release and does not require activation of adenylyl cyclase, These findings indicate that a novel form of synaptic plasticity might underlie learning in the avian hippocampus.

Excitatory synaptic inputs to pyramidal neurons of the lateral amygdala

Whole-cell patch clamp recordings were made from pyramidal neurons in the rat lateral amygdala (LA). Synaptic currents were evoked by stimulating in either the external capsule (ec), internal capsule (ic) or basolateral nucleus (BLA). Stimulation of either the ic, ec or BLA evoked a glutamatergic excitatory synaptic current (EPSC) which was mediated by both non-NMDA and NMDA (N-methyl-D-aspartic acid) receptors, The ratio of the amplitude of the NMDA receptor-mediated component measured at +40 mV to the amplitude of the alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) component measured at -60 mV was similar regardless of whether EPSCs were evoked in the ec, ic or BLA. At resting membrane potentials, excitatory synaptic potentials evoked from either the ec or putative thalamic inputs were unaffected by application of the NMDA receptor antagonist APV. Spontaneous glutamatergic currents had two components to their decay phase. The slow component was selectively blocked by the NMDA receptor antagonist D-APV, indicating that AMPA and NMDA receptors are colocalized in spiny neurons. We conclude that pyramidal cells of the LA receive convergent inputs from the cortex, thalamus and basal nuclei. At all inputs, both AMPA/kainate and NMDA-type receptors are active and colocalized in the postsynaptic density.

Loss of connectivity in Alzheimer's disease: an evaluation of white matter tract integrity with colour coded MR diffusion tensor imaging

A novel MRI method-diffusion tensor imaging-was used to compare the integrity of several white matter fibre tracts in patients with probable Alzheimer's disease. Relative to normal controls, patients with probable Alzheimer's disease showed a highly significant reduction in the integrity of the association white matter fibre tracts, such as the splenium of the corpus callosum, superior longitudinal fasciculus, and cingulum. By contrast, pyramidal tract integrity seemed unchanged. This novel finding is consistent with the clinical presentation of probable Alzheimer's disease, in which global cognitive decline is a more prominent feature than motor disturbance.

Excitatory synaptic transmission in the lateral and central amygdala

The amygdala plays a major role in the acquisition and expression of fear conditioning. NMDA receptor-dependent synaptic plasticity within the basolateral amygdala has been proposed to underlie the acquisition and possible storage of fear memories. Here the properties of fast glutamatergic transmission in the lateral and central nuclei of the amygdala are presented. In the lateral amygdala, two types of neurons, interneurons and projection neurons, could be distinguished by their different firing properties. Glutamatergic inputs to interneurons activated AMPA receptors with inwardly rectifying current-voltage relations (I-Vs), whereas inputs to projection neurons activated receptors that had linear I-Vs, indicating that receptors on interneurons lack GluR2 subunits. Inputs to projection neurons formed dual component synapses with both AMPA and NMDA components, whereas at inputs to interneurons, the contribution of NMDA receptors was very small. Neurons in the central amygdala received dual component glutamatergic inputs that activated AMPA receptors with linear I-Vs. NMDA receptor-mediated EPSCs had slow decay time constants in the central nucleus. Application of NR2B selective blockers ifenprodil or CP-101,606 blocked NMDA EPSCs by 70% in the central nucleus, but only by 30% in the lateral nucleus. These data show that the distribution of glutamatergic receptors on amygdalar neurons is not uniform. In the lateral amygdala, interneurons and pyramidal neurons express AMPA receptors with different subunit compositions. Synapses in the central nucleus activate NMDA receptors that contain NR1 and NR2B subunits, whereas synapses in the lateral nucleus contain receptors with both NR2A and NR2B subunits.

Development and subunit composition of synaptic NMDA receptors in the amygdala: NR2B Synapses in the adult central amygdala

NMDA receptors are well known to play an important role in synaptic development and plasticity. Functional NMDA receptors are heteromultimers thought to contain two NR1 subunits and two or three NR2 subunits. In central neurons, NMDA receptors at immature glutamatergic synapses contain NR2B subunits and are largely replaced by NR2A subunits with development. At mature synapses, NMDA receptors are thought to be multimers that contain either NR1/NR2A or NR1/NR2A/NR2B subunits, whereas receptors that contain only NR1/NR2B subunits are extrasynaptic. Here, we have studied the properties of NMDA receptors at glutamatergic synapses in the lateral and central amygdala. We find that NMDA receptor-mediated synaptic currents in the central amygdala in both immature and mature synapses have slow kinetics and are substantially blocked by the NR2B-selective antagonists (1S, 2S)-1-(4-hydroxyphenyl)-2-(4-hydroxy-4-phenylpiperidino)-1-propano and ifenprodil, indicating that there is no developmental change in subunit composition. In contrast, at synapses on pyramidal neurons in the lateral amygdala, whereas NMDA EPSCs at immature synapses are slow and blocked by NR2B-selective antagonists, at mature synapses their kinetics are faster and markedly less sensitive to NR2B-selective antagonists, consistent with a change from NR2B to NR2A subunits. Using real-time PCR and Western blotting, we show that in adults the ratio of levels of NR2B to NR2A subunits is greater in the central amygdala than in the lateral amygdala. These results show that the subunit composition synaptic NMDA receptors in the lateral and central amygdala undergo distinct developmental changes.

Altered inhibitory synaptic transmission in superficial dorsal horn neurones in spastic and oscillator mice

The spastic (spa) and oscillator (ot) mouse have naturally occurring mutations in the inhibitory glycine receptor (GlyR) and exhibit severe motor disturbances when exposed to unexpected sensory stimuli. We examined the effects of the spa and ot mutations on GlyR- and GABA(A)R-mediated synaptic transmission in the superficial dorsal horn (SFDH), a spinal cord region where inhibition is important for nociceptive processing. Spontaneous mIPSCs were recorded from visually identified neurones in parasagittal spinal cord slices. Neurones received exclusively GABA(A)R-mediated mIPSCs, exclusively GlyR-mediated mIPSCs or both types of mIPSCs. In control mice (wild-type and spa/+) over 40 % of neurones received both types of mIPSCs, over 30 % received solely GABA(A)R-mediated mIPSCs and the remainder received solely GlyR-mediated mIPSCs. In spa/spa animals, 97 % of the neurones received exclusively GABA(A)ergic or both types of mIPSCs. In ot/ot animals, over 80 % of the neurones received exclusively GABA(A)R-mediated mIPSCs. GlyR-mediated mIPSC amplitude and charge were reduced in spa/spa and ot/ot animals. GABA,Rmediated mIPSC amplitude and charge were elevated in spa/spa but unaltered in ot/ot animals. GlyR- and GABA(A)R-mediated mIPSC decay times were similar for all genotypes, consistent with the mutations altering receptor numbers but not kinetics. These findings suggest the spastic and oscillator mutations, traditionally considered motor disturbances, also disrupt inhibition in a sensory region associated with nociceptive transmission. Furthermore, the spastic mutation results in a compensatory increase in GABA(A)ergic transmission in SFDH neurones, a form of inhibitory synaptic plasticity absent in the oscillator mouse.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

White matter microstructure underlying default mode network connectivity in the human brain

Resting state functional magnetic resonance imaging (fMRI) reveals a distinct network of correlated brain function representing a default mode state of the human brain The underlying structural basis of this functional connectivity pattern is still widely unexplored We combined fractional anisotropy measures of fiber tract integrity derived from diffusion tensor imaging (DTI) and resting state fMRI data obtained at 3 Tesla from 20 healthy elderly subjects (56 to 83 years of age) to determine white matter microstructure e 7 underlying default mode connectivity We hypothesized that the functional connectivity between the posterior cingulate and hippocampus from resting state fMRI data Would be associated with the white matter microstructure in the cingulate bundle and fiber tracts connecting posterior cingulate gyrus With lateral temporal lobes, medial temporal lobes, and precuneus This was demonstrated at the p<0001 level using a voxel-based multivariate analysis of covariance (MANCOVA) approach In addition, we used a data-driven technique of joint independent component analysis (ICA) that uncovers spatial pattern that are linked across modalities. It revealed a pattern of white matter tracts including cingulate bundle and associated fiber tracts resembling the findings from the hypothesis-driven analysis and was linked to the pattern of default mode network (DMN) connectivity in the resting state fMRI data Out findings support the notion that the functional connectivity between the posterior cingulate and hippocampus and the functional connectivity across the entire DMN is based oil distinct pattern of anatomical connectivity within the cerebral white matter (C) 2009 Elsevier Inc All rights reserved

An fMRI Normative Database for Connectivity Networks Using One-Class Support Vector Machines

The application of functional magnetic resonance imaging (fMRI) in neuroscience studies has increased enormously in the last decade. Although primarily used to map brain regions activated by specific stimuli, many studies have shown that fMRI can also be useful in identifying interactions between brain regions (functional and effective connectivity). Despite the widespread use of fMRI as a research tool, clinical applications of brain connectivity as studied by fMRI are not well established. One possible explanation is the lack of normal pattern, and intersubject variability-two variables that are still largely uncharacterized in most patient populations of interest. In the current study, we combine the identification of functional connectivity networks extracted by using Spearman partial correlation with the use of a one-class support vector machine in order construct a normative database. An application of this approach is illustrated using an fMRI dataset of 43 healthy Subjects performing a visual working memory task. In addition, the relationships between the results obtained and behavioral data are explored. Hum Brain Mapp 30:1068-1076, 2009. (C) 2008 Wiley-Liss. Inc.

The impact of functional connectivity changes on support vector machines mapping of fMRI data

Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.

Right Orbitofrontal Corticolimbic and Left Corticocortical White Matter Connectivity Differentiate Bipolar and Unipolar Depression

Objectives: The absence of pathophysiologically relevant diagnostic markers of bipolar disorder (BD) leads to its frequent misdiagnosis as unipolar depression (UD). We aimed to determine whether whole brain white matter connectivity differentiated BD from UD depression. Methods: We employed a three-way analysis of covariance, covarying for age, to examine whole brain fractional anisotropy (FA), and corresponding longitudinal and radial diffusivity, in currently depressed adults: 15 with BD-type I (mean age 36.3 years, SD 12.0 years), 16 with recurrent UD (mean age 32.3 years, SD 10.0 years), and 24 healthy control adults (HC) (mean age 29.5 years, SD 9.43 years). Depressed groups did not differ in depression severity, age of illness onset, and illness duration. Results: There was a main effect of group in left superior and inferior longitudinal fasciculi (SLF and ILF) (all F >= 9.8; p <= .05, corrected). Whole brain post hoc analyses (all t >= 4.2; p <= .05, corrected) revealed decreased FA in left SLF in BD, versus UD adults in inferior temporal cortex and, versus HC, in primary sensory cortex (associated with increased radial and decreased longitudinal diffusivity, respectively); and decreased FA in left ILF in UD adults versus HC. A main effect of group in right uncinate fasciculus (in orbitofrontal cortex) just failed to meet significance in all participants but was present in women. Post hoc analyses revealed decreased right uncinate fasciculus FA in all and in women, BD versus HC. Conclusions: White matter FA in left occipitotemporal and primary sensory regions supporting visuospatial and sensory processing differentiates BD from UD depression. Abnormally reduced FA in right fronto-temporal regions supporting mood regulation, might underlie. predisposition to depression in BD. These measures might help differentiate pathophysiologic processes of BD versus UD depression.

Abnormal Left and Right Amygdala-Orbitofrontal Cortical Functional Connectivity to Emotional Faces: State Versus Trait Vulnerability Markers of Depression in Bipolar Disorder

Background: Amygdala-orbitofrontal cortical (OFC) functional connectivity (FC) to emotional stimuli and relationships with white matter remain little examined in bipolar disorder individuals (BD). Methods: Thirty-one BD (type 1; n = 17 remitted; n = 14 depressed) and 24 age- and gender-ratio-matched healthy individuals (HC) viewed neutral, mild, and intense happy or sad emotional faces in two experiments. The FC was computed as linear and nonlinear dependence measures between amygdala and OFC time series. Effects of group, laterality, and emotion intensity upon amygdala-OFC FC and amygdala-OFC FC white matter fractional anisotropy (FA) relationships were examined. Results: The BD versus HC showed significantly greater right amygdala-OFC FC (p <= .001) in the sad experiment and significantly reduced bilateral amygdala-OFC FC (p = .007) in the happy experiment. Depressed but not remitted female BD versus female HC showed significantly greater left amygdala-OFC FC (p = .001) to all faces in the sad experiment and reduced bilateral amygdala-OFC FC to intense happy faces (p = .01). There was a significant nonlinear relationship (p = .001) between left amygdala-OFC FC to sad faces and FA in HC. In BD, antidepressants were associated with significantly reduced left amygdala-OFC FC to mild sad faces (p = .001). Conclusions: In BD, abnormally elevated right amygdala-OFC FC to sad stimuli might represent a trait vulnerability for depression, whereas abnormally elevated left amygdala-OFC FC to sad stimuli and abnormally reduced amygdala-OFC FC to intense happy stimuli might represent a depression state marker. Abnormal FC measures might normalize with antidepressant medications in BD. Nonlinear amygdala-OFC FC-FA relationships in BID and HC require further study.

Abnormally increased effective connectivity between parahippocampal gyrus and ventromedial prefrontal regions during emotion labeling in bipolar disorder

Emotional liability and mood dysregulation characterize bipolar disorder (BID), yet no study has examined effective connectivity between parahippocampal gyrus and prefrontal cortical regions in ventromedial and dorsal/lateral neural systems subserving mood regulation in BD. Participants comprised 46 individuals (age range: 18-56 years): 21 with a DSM-IV diagnosis of BID, type I currently remitted; and 25 age- and gender-matched healthy controls (HC). Participants performed an event-related functional magnetic resonance imaging paradigm, viewing mild and intense happy and neutral faces. We employed dynamic causal modeling (I)CM) to identify significant alterations in effective connectivity between BD and HC. Bayes model selection was used to determine the best model. The right parahippocampal gyrus (PHG) and right subgenual cingulate gyrus (sgCG) were included as representative regions of the ventromedial neural system. The right dorsolateral prefrontal cortex (DLPFC) region was included as representative of the dorsal/lateral neural system. Right PHG-sgCG effective connectivity was significantly greater in BD than HC, reflecting more rapid, forward PHG-sgCG signaling in BD than HC. There was no between-group difference in sgCG-DLPFC effective connectivity. In BD, abnormally increased right PHG-sgCG effective connectivity and reduced right PHG activity to emotional stimuli suggest a dysfunctional ventromedial neural system implicated in early stimulus appraisal, encoding and automatic regulation of emotion that may represent a pathophysiological functional neural mechanism for mood dysregulation in BD. (C) 2009 Elsevier Ireland Ltd. All rights reserved.