text:
The Relationship between Working Memory Storage and Elevated Activity as Measured with Functional Magnetic Resonance Imaging.
ABSTRACT Does the sustained, elevated neural activity observed during working memory tasks reflect the short-term retention of information? Functional magnetic resonance imaging (fMRI) data of delayed recognition of visual motion in human participants were analyzed with two methods: a general linear model (GLM) and multivoxel pattern analysis. Although the GLM identified sustained, elevated delay-period activity in superior and lateral frontal cortex and in intraparietal sulcus, pattern classifiers were unable to recover trial-specific stimulus information from these delay-active regions. The converse-no sustained, elevated delay-period activity but successful classification of trial-specific stimulus information-was true of posterior visual regions, including area MT+ (which contains both middle temporal area and medial superior temporal area) and calcarine and pericalcarine cortex. In contrast to stimulus information, pattern classifiers were able to extract trial-specific task instruction-related information from frontal and parietal areas showing elevated delay-period activity. Thus, the elevated delay-period activity that is measured with fMRI may reflect processes other than the storage, per se, of trial-specific stimulus information. It may be that the short-term storage of stimulus information is represented in patterns of (statistically) "subthreshold" activity distributed across regions of low-level sensory cortex that univariate methods cannot detect.
Article: Fine-Grained, Local Maps and Coarse, Global Representations Support Human Spatial Working Memory
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ABSTRACT: While sensory processes are tuned to particular features, such as an object's specific location, color or orientation, visual working memory (vWM) is assumed to store information using representations, which generalize over a feature dimension. Additionally, current vWM models presume that different features or objects are stored independently. On the other hand, configurational effects, when observed, are supposed to mainly reflect encoding strategies. We show that the location of the target, relative to the display center and boundaries, and overall memory load influenced recall precision, indicating that, like sensory processes, capacity limited vWM resources are spatially tuned. When recalling one of three memory items the target distance from the display center was overestimated, similar to the error when only one item was memorized, but its distance from the memory items' average position was underestimated, showing that not only individual memory items' position, but also the global configuration of the memory array may be stored. Finally, presenting the non-target items at recall, consequently providing landmarks and configurational information, improved precision and accuracy of target recall. Similarly, when the non-target items were translated at recall, relative to their position in the initial display, a parallel displacement of the recalled target was observed. These findings suggest that fine-grained spatial information in vWM is represented in local maps whose resolution varies with distance from landmarks, such as the display center, while coarse representations are used to store the memory array configuration. Both these representations are updated at the time of recall.PLoS ONE 09/2014; · 3.53 Impact Factor - SourceAvailable from: Johan Eriksson[Show abstract] [Hide abstract]
ABSTRACT: Conscious processing is generally seen as required for flexible and willful actions, as well as for tasks that require durable information maintenance. Here we present research that questions the assumption that only consciously perceived information is durable (>500 ms). Using the attentional blink (AB) phenomenon, we rendered otherwise relatively clearly perceived letters non-conscious. In a first experiment we systematically manipulated the delay between stimulus presentation and response, for the purpose of estimating the durability of non-conscious perceptual representations. For items reported not seen, we found that behavioral performance was better than chance across intervals up to 15 s. In a second experiment we used fMRI to investigate the neural correlates underlying the maintenance of non-conscious perceptual representations. Critically, the relatively long delay period demonstrated in experiment 1 enabled isolation of the signal change specifically related to the maintenance period, separate from stimulus presentation and response. We found sustained BOLD signal change in the right mid-lateral prefrontal cortex, orbitofrontal cortex, and crus II of the cerebellum during maintenance of non-consciously perceived information. These findings are consistent with the controversial claim that working-memory mechanisms are involved in the short-term maintenance of non-conscious perceptual representations.Frontiers in Human Neuroscience 11/2014; 8:938: 1-10. · 2.90 Impact Factor -
Article: The bandwidth of consolidation into visual short-term memory (VSTM) depends on the visual feature.
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ABSTRACT: We investigated the nature of the bandwidth limit in the consolidation of visual information into visual short-term memory. In the first two experiments, we examined whether previous results showing differential consolidation bandwidth for color and orientation resulted from methodological differences by testing the consolidation of color information with methods used in prior orientation experiments. We briefly presented two color patches with masks, either sequentially or simultaneously, followed by a location cue indicating the target. Participants identified the target color via button-press (Experiment 1) or by clicking a location on a color wheel (Experiment 2). Although these methods have previously demonstrated that two orientations are consolidated in a strictly serial fashion, here we found equivalent performance in the sequential and simultaneous conditions, suggesting that two colors can be consolidated in parallel. To investigate whether this difference resulted from different consolidation mechanisms or a common mechanism with different features consuming different amounts of bandwidth, Experiment 3 presented a color patch and an oriented grating either sequentially or simultaneously. We found a lower performance in the simultaneous than the sequential condition, with orientation showing a larger impairment than color. These results suggest that consolidation of both features share common mechanisms. However, it seems that color requires less information to be encoded than orientation. As a result two colors can be consolidated in parallel without exceeding the bandwidth limit, whereas two orientations or an orientation and a color exceed the bandwidth and appear to be consolidated serially.Visual Cognition 08/2014; 22(7):920-947. · 2.05 Impact Factor
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The relation between working memory storage and elevated
activity, as measured with fMRI
Adam C. Riggall1 and Bradley R. Postle1,2
1Department of Psychology, University of Wisconsin-Madison, Madison, Wisconsin, 53706
2Department of Psychiatry, University of Wisconsin-Madison, Madison, Wisconsin, 53706
Does the sustained, elevated neural activity observed during working memory (WM) tasks reflect
the short-term retention of information? Functional magnetic resonance imaging (fMRI) data of
delayed-recognition of visual motion in human participants were analyzed with two methods, a
general linear model (GLM) and multi-voxel pattern analysis (MVPA). Although the GLM
identified sustained, elevated delay-period activity in superior and lateral frontal cortex and in
intraparietal sulcus (IPS), pattern classifiers were unable to recover trial-specific stimulus
information from these delay-active regions. The converse—no sustained, elevated delay-period
activity, but successful classification of trial-specific stimulus information—was true of posterior
visual regions, including MT+ and calcarine and pericalcarine cortex. In contrast to stimulus
information, pattern classifiers were able to extract trial-specific task instruction-related
information from frontal and parietal areas showing elevated delay-period activity. Thus, the
elevated delay-period activity that is measured with fMRI may reflect processes other than the
storage, per se, of trial-specific stimulus information. It may be that the short-term storage of
stimulus information is represented in patterns of (statistically) "subthreshold" activity distributed
across regions of low-level sensory cortex that univariate methods cannot detect.
For decades, a prevailing view has been that working memory (WM) storage is
accomplished via sustained, elevated neural activity. Such activity, first identified with
extracellular recordings in the non-human primate (Fuster and Alexander, 1971; Niki, 1974;
Funahashi et al., 1989), has been observed in numerous areas of the human brain with
functional magnetic resonance imaging (fMRI; Curtis and D'Esposito, 2003). The idea of a
role for delay-period activity in storage is reinforced by its sensitivity to manipulation of
memory-influencing factors, such as persistence across varying delay lengths, and variation
of signal magnitude with memory load (Vogel and Machizawa, 2004; Xu and Chun, 2006;
Postle, 2006).
There are, however, complications with the mnemonic interpretation of delay-period
activity. One is cases of activity that appear mnemonic, but can be shown to support other
functions, such as attention or response preparation (Fuster, 2002; Lebedev et al., 2004).
Relatedly, lesion-induced deficits originally interpreted as mnemonic (Jacobson, 1936;
Funahashi et al., 1993) have subsequently been reinterpreted as reflecting factors other than
memory per se (Malmo, 1942; Tsujimoto and Postle, 2012).
Corresponding Author: Adam C. Riggall, (firstname.lastname@example.com).
The authors declare no conflicts of interest
NIH Public Access
Author Manuscript
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Published in final edited form as:
J Neurosci. 2012 September 19; 32(38): 12990–12998. doi:10.1523/JNEUROSCI.1892-12.2012.
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A second complication is that delay-period activity can fail to show properties thought
necessary for a mnemonic signal. In one such case, although fMRI activity at several sites
was elevated throughout a long delay period (24 seconds), none showed load sensitivity,
leaving uncertain these regions contribution to storage (Jha and McCarthy, 2000). In
another, monkeys showed excellent short-term memory (STM) for direction of motion
despite the absence of directionally tuned neurons in either the middle temporal area (MT)
or the prefrontal cortex (PFC) that sustained elevated activity across the delay (Bisley et al.,
2004; Zaksas and Pasternak, 2006; Hussar and Pasternak, 2012).
A third complication relates to assumptions of homogeneity of function, often only implied
or tacit, but nonetheless inherent, in massively univariate analyses of neuroimaging data.
When activity is identified in a large volume of "activated" tissue, the extraction of a
spatially averaged signal from contiguous voxels necessarily assumes that all are "doing the
same thing". Further, its interpretation entails assuming that this locally homogeneous
activity can be construed as supporting a mental function independent of other brain areas.
These assumptions, however, are difficult to reconcile with the increasingly common
recognition that neural representations are high-dimensional and supported by anatomically
distributed, dynamic computations (Norman et al., 2006; Kriegeskorte et al., 2006; Bullmore
and Sporns, 2009; Cohen, 2011).
Given these complications, we sought to test core assumptions about elevated delay-period
fMRI activity using an information-based analysis. Multivariate pattern classification was
used to test two hypotheses about STM for visual motion information: 1) that elevated
delay-period activity carries trial-specific stimulus information, and 2) that trial-specific
stimulus information can be encoded in subthreshold patterns of activity. The first tests an
assumption that has underlain most neuroimaging research on WM. Confirmation of the
second would extend findings for visual STM for oriented gratings (Serences et al., 2009;
Harrison and Tong, 2009) and offer insight about the physiological basis of STM for visual
motion (Hussar and Pasternak, 2012).
Materials and Methods
To test our hypotheses we scanned subjects (fMRI) while they performed a delayed-
recognition task for visual motion (Fig. 1). We then trained pattern classifiers to discriminate
the direction of motion from individual time points in the trial and tested to see how these
classifiers labeled the data from all the other time points during the trial (creating a decoding
time series). A similar approach has been shown to be sensitive to the dynamics of memory
content, capturing changes in the memory trace on a continuous basis throughout the trial
(Polyn et al., 2005; Lewis-Peacock and Postle, 2008, 2012).
In contrast to analysis methods that assess the magnitude of activity (whether the firing rate
of a neuron or the strength of the blood-oxygen level-dependent (BOLD) signal of one or a
group of voxels), information-based analyses, such as pattern classification, focus on
obtaining quantitative measures of the information content within a given area (Kriegeskorte
et al., 2006; Kriegeskorte, 2011). This approach, often termed multi-voxel pattern analysis
(MVPA), uses machine learning methods to identify patterns of activity that are reliably
associated with different stimuli or categories of stimuli. The extent to which novel patterns
of activity can then be correctly categorized provides a measure of the information available
in the underlying voxels (Norman et al., 2006; Haynes, 2011; Jimura and Poldrack, 2012).
Ten volunteers (5 females) between 21 and 28 years of age (mean 23.8 years) were recruited
from the undergraduate and graduate student community of the University of Wisconsin-
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Madison and paid for their participation. All subjects had normal or corrected-to-normal
vision, no reported history of neurological disease, and no other contraindications for MRI.
All subjects gave written informed consent according to the procedures approved by the
Health Sciences Institutional Review Board at the University of Wisconsin-Madison. Three
subjects (1 female) were excluded from the Results due to failure to perform the task to
criterion level (see Results for more details).
Behavioral Paradigm
Participants were scanned while performing seven runs of a delayed-recognition task for
visual motion. A schematic representation of the experiment is illustrated in Fig. 1. Each
trial began with a fixation cross changing color to white, indicating to subjects that they
needed to fixate the cross and prepare for the start of the trial. After 1.5 s a patch of
coherently moving dots was presented (sample, 1 s). Participants were instructed to
remember both the direction and the speed of this motion while maintaining fixation for the
duration of the trial. The sample was followed by a 15 s delay-period. Seven seconds into
the delay period the fixation cross changed color to indicate the dimension on which
subjects would be making a match/non-match comparison judgement between the
remembered motion and a new set of moving dots; blue indicated they should make the
judgement based on the direction of the moving dots, ignoring speed, while magenta
indicated that they should make the judgement based on speed, ignoring direction.
Following the delay, a second patch of coherently moving dots (probe, 1 s) was presented
and subjects were required to indicate as quickly as possible with one of two buttons if the
probe motion matched or did not match the sample on the cued dimension. After a 1 s
response period the fixation cross changed color to green if the subjects were correct or red
if they were incorrect (feedback, 2 s). A 10 s intertrial interval (ITI) followed, during which
the fixation cross changed color to gray and subjects were instructed they could break
fixation and relax their eyes.
Sample and probe stimuli consisted of circular patches (15° diameter) of coherently moving
dots. Sample motion could be in one of four directions (42°, 132°, 222°, 312°) and at one of
three speeds (4°/s, 8°/s, 12°/s). Directions were chosen to be off the cardinal axes to reduce
potential verbalizations. Probe stimuli on match trials had the same value in the cued
dimension, and a different value from the non-cued dimension (e.g., for a match trial where
direction was cued the sample might have moved toward 132° at 8°/s, while the matching
probe might have moved toward 132° at 4°/s). On direction-cued non-match trials the probe
stimulus was rotated (randomly clockwise or counter-clockwise) by a degree threshold value
from the direction of sample and the speed was randomly drawn from one of the two values
not used in the sample. On speed-cued non-match trials the probe stimulus speed was
changed (randomly increased or decreased) by a proportional threshold value from the speed
of the sample and the direction was randomly drawn from one of the three values not used in
the sample. The threshold values for non-match direction and speed were updated using
separate adaptive staircases (Levitt, 1971) to keep performance around 75% correct. The
logic of this approach was that by holding task difficulty constant throughout an
experimental session, we could assume comparable fidelity of representation on trials for
which the response ended up being correct versus incorrect. This would maximize
sensitivity by allowing inclusion of all trials in the analyses. Before scanning, subjects
practiced a block of 24 trials to familiarize themselves with the experimental procedure and
to determine starting threshold values for non-match trials.
Participants completed 168 trials over the course of 7 runs while in the scanner. Sample
stimuli included all possible pairwise combinations of directions and speeds (12 different
combinations, each seen 14 times). Direction was cued on 96 trials, with the remaining 72
cued for speed. This disparity balanced the overall number of individual examples at each
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dimension value across the cued dimensions. Match and non-match trials were equally
likely. The experimental stimuli were controlled by E-Prime 2.0 (Psychology Software
Tools, Inc., PA) and viewed through fiber-optic goggles mounted on the head coil (Avotec
Visible Eye, Stuart, FL). Participants responded via two buttons on a fiber-optic button box
(Psychology Software Tools, Inc., PA).
Subjects also performed one block of an MT+ localalizer task, similar to that used by Huk et
al. (2002). In summary, participants viewed alternating 18 second blocks of stationary and
moving dot patterns (alternating from expanding and contracting every second) within a
circular aperture (15°) while maintaining fixation, for a total of 8 blocks of each.
Data Acquisition and Preprocessing
Whole brain images were acquired with the 3T scanner (Discovery MR750; GE Healthcare)
at the Lane Neuroimaging Laboratory at the University of Wisconsin-Madison. For all
subjects a high-resolution T1-weighted image was acquired with an FSPGR sequence (8.132
ms TR, 3.18 ms TE, 12° flip angle,156 axial slices, 256 × 256 in-plane, 1.0 mm isotropic). A
gradient-echo, echo-planar sequence (2 s TR, 25 ms TE) was used to acquire data sensitive
to the BOLD signal within a 64 × 64 matrix (39 sagittal slices, 3.5 mm isotropic). Seven
runs of the delayed-recognition task were obtained for each subject, each lasting 12 min, 8
sec (364 volumes). All task runs were preceded by 10 sec of dummy pulses to achieve a
steady state of tissue magnetization. One run of the MT+ localizer was obtained for each
subject, lasting 4.8 minutes (144 volumes).
The functional data were preprocessed using the Analysis of Functional NeuroImages
(AFNI) software package (Cox, 1996). All volumes were spatially aligned to the final
volume of the final run using a rigid-body realignment and corrected for slice time
acquisition. Linear, quadratic and cubic trends were removed from each run to reduce the
influence of scanner drift. For univariate analyses, data were spatially smoothed with a 6
mm FWHM Gaussian kernel and transformed into Talairach space (Talairach and Tournoux,
1988). For classification analyses, data were z-scored separately within run for each voxel.
Data were not smoothed and were left in their native space.
Univariate Analyses
Each within-trial event of the delayed-recognition task (i.e., sample, pre-cue delay, cue,
post-cue delay, probe, response) was modeled separately for direction- and speed- cued
trials. Sample and probe were modeled as 1 s boxcars, each delay as a boxcar of appropriate
duration, and the cue and response as impulses. All were convolved with a canonical
hemodynamic response function (HRF). Each of these independent regressors was entered
into a modified general linear model (GLM) for analysis using AFNI. For the present
purposes, a more generous boxcar-shaped covariate was used to model the delay-periods
(rather than a more conservative mid-delay delta function (Zarahn et al., 1999; Postle et al.,
2000)), to ensure that we would not miss any delay-active voxels, although at the expense of
likely also being sensitive to some variance that is attributable to the sample presentation. In
this way, we implemented a generous feature selection step that included as many "delay
active" voxels as possible for MVPA, thereby being careful not to exclude any such voxels
that may potentially carry stimulus-specific information. The localizer was modeled with
boxcars for both stationary and moving dot patterns. This localizer was used to insure that
the regions of interest used for the MVPA analysis included MT+.
Pattern Classi cation Analyses
Classification was performed using the Princeton Multi-Voxel Pattern Analysis
(www.pni.princeton.edu/mvpa) toolbox and custom routines in MATLAB (The MathWorks,
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Natick, MA, USA). Preprocessed fMRI data from individual trial time points were used to
train separate classifiers to classify the direction of motion (4 possible directions) or the
speed of motion (3 possible speeds) in the sample and by inference, the direction/speed of
motion in memory (stimulus-specific classification), or to classify whether the subject had
been cued that direction or speed was the relevant dimension on a given trial (trial-
dimension classification).
Classification was accomplished using L2-regularized logistic regression (LR), a linear
classification approach used widely in the machine learning community and well suited for
application to fMRI data as it tends to generalize well after learning in high-dimensional
feature spaces with limited training examples (Pereira et al., 2009). The lambda penalty
term, which reduces the contribution of less informative voxels to classification and thus
improves generalization, was determined (λ = 25) by repeating the wholebrain testing
procedure described below for penalty terms at powers of 10 from −4 to 4, then at a finer
grained resolution within the best interval. The penalty term was chosen to maximize the
mean decoding performance across all subjects. During decoding, a trial was considered
correctly classified if the correct direction/speed had the highest likelihood estimate (winner-
take-all classification). Overall classification accuracy was determined using leave-one-trial-
out cross-validation, in which the classifier was repeatedly trained on data from all but one
trial, and then tested on the left out trial, rotating through all the trials as the left out testing
Stimulus-specific classifiers were always trained with data from direction-cued trials or
speed-cued trials, never both. Testing of trained classifiers was done on trials of both type.
This allowed us to compare how representations changed when subjects were cued that they
would be judging speed, and thus direction was no longer relevant, and vice versa. Trial-
dimension classifiers were trained and tested on all data.
In order to examine the dynamics of the memory trace, each classifier was trained using data
from only a single time point in the trial (e.g., the first volume acquisition following the
target) and then tested on all time points in the left-out trial (i.e., including both time points
preceding and following the training time point). The result of this procedure is a time
course of decoding accuracy for the entire trial. By doing the initial training of the classifier
using different time points in the trial (e.g., a time point just after the sample, a time point in
the later part of the delay, etc.), it was possible to estimate the stability of a given
representation throughout the duration of the trial.
Classification was initially performed on whole brain data that had undergone a basic
feature-selection step whereby only those voxels that showed a main effect for task (t > 2) in
the univariate GLM were included. This step was included to reduce the chances of
overfitting during training. Subsequent Region of Interest (ROI)-based analyses used only
those voxels within individual ROIs, created from the intersection of anatomically defined
ROIs and voxels that showed either significant sustained delay-period activity or no delay-
period activity, depending on the specific hypothesis. Four anatomically defined ROIs were
hand drawn for each subject by tracing gray matter on the high-resolution anatomical scans:
frontal, parietal, lateral occipital and temporal, and medial occipital. The frontal region
included the entire precentral sulcus (PCS) and the posterior portion of the inferior frontal
sulcus (IFS). For finer-grained analyses, this was subdivided into three frontal ROIs that
showed robust delay-period activity: the superior rostral bank of the PCS bounded
superiorly by the intersection of the superior frontal sulcus (SFS); a more inferior portion of
the rostral bank of the PCS bounded ventrally by the intersection with the IFS; and the
caudal third of the IFS. The parietal region included the entire intraparietal sulcus (IPS) and
the superior parietal lobule (SPL). For finer-grained analyses, it was also subdivided into
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three ROIs: medial-caudal IPS comprising the descending segment and the caudal half of the
horizontal segment, dorsolateral IPS comprising the rostral half of the horizontal segment
and the ascending segment, and SPL. The lateral occipital and temporal region included all
of the lateral occipital gyrus, the fusiform gyrus, the posterior portion of the middle and
inferior temporal gyri and the posterior portion of the inferior temporal sulcus. The medial
occipital region covered the medial portion of the occipital lobe from the lingual sulcus to
the occipitoparietal sulcus, including all of the calcarine sulcus.
The significance of classifier performance was determined using a random permutation test
(Golland and Fischl, 2003) to determine the likelihood of observing a specific accuracy
under the null hypothesis that there is no relationship between the data and the specific class
labels used to train the classifier (directions/speeds of motion). A null distribution was
generated by rerunning the entire classification cross-validation procedure 1000 times,
randomly shuffling the class labels each time. A p-value was then computed by determining
the proportion of permuted accuracies that were higher than the observed accuracy. This
procedure was repeated for all classification results.
Behavioral Results
Task difficulty was equated across subjects by feeding real-time, trial-by-trial performance
information to a staircasing algorithm that dynamically adjusted the difficulty of non-
matching probe stimuli (direction and speed independently) so as to maintain performance at
a target level of 75% correct. Overall mean behavioral performance (n = 7) was 80.38%
correct for direction trials and 80.32% correct for speed trials, both slightly better than the
target performance level because several subjects reached a predefined minimum threshold
value, at which point the staircase procedure could no longer reduce the threshold to further
increase task difficulty. The average non-match direction threshold was 10.9° (SD 5.33°).
The average non-match speed threshold was a 38% change (SD 15.3%). Three subjects were
dropped from the study because their inordinately high thresholds indicated that they were
responding at random.
Univariate Results
To test the first hypothesis, that elevated delay-period activity carries trial-specific stimulus
information and can thus be interpreted as a neural correlate of memory storage, we first
identified areas showing elevated, sustained delay-period activity by solving a massively
univariate GLM for each subject. The resultant individual thresholded statistical maps were
then used, on a subject-by-subject basis, to select the voxels used for training the classifiers.
Group-level statistical maps for the sample-evoked (Fig. 2A) and delay-period (Fig. 2B)
activity illustrate several important characteristics. Activity evoked by the sample was
widespread, located bilaterally in posterior visual areas, lateral occipitotemporal regions
including the inferior temporal sulcus (including the putative MT+ complex identified with
the localizer), IPS, posterior IFS and SFS, and PCS. Delay-period activity was more
circumscribed, with clusters of significant activity (p < 0.05, FDR corrected) bilaterally in
the IPS, IFS, and PCS. This pattern of elevated activity agrees with many other findings
from studies of visuo-spatial WM (Curtis and D'Esposito, 2003).
Whole Brain Pattern Classification
Before directly testing our hypotheses, it was necessary to demonstrate that motion
information could be decoded on a time point-by-time point basis. All analyses were
performed on single-subject data, with statistical reliability subsequently assessed across the
sample. For each subject's data, a set of four classifiers was trained to discriminate the
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direction of the sample motion stimulus (and by inference, the remembered motion
direction; 4 possible directions), each using feature-selected whole-brain data from
direction-cued trials and restricted to a single time point within the trial. The first classifier
(Sample) was trained on data from only the time point 4 seconds after the sample onset,
which corresponds to the peak of the sample-evoked response. The second classifier (Late
Delay) was trained on data from the time point 16 seconds after sample onset, corresponding
to the post-cue portion of the delay period, prior to the onset of the probe stimulus. The third
classifier (Probe) was trained on data from the time point 20 seconds after sample onset (4
seconds after probe onset), corresponding to the peak of the probe-evoked response. The
final classifier (ITI) was trained on data from the time point 26 seconds after sample onset,
corresponding to the middle of the intertrial interval. This classifier was included as a
control, as we would not expect there to be any stimulus-specific information retained once
the trial had been completed.
Each trained classifier was then used to construct a decoding time course of direction
representation on every trial time point from the held-out direction-cued trials. This
approach allowed us to detect changes in the neural representation of information across the
trial. For example, by training a classifier on data from very early in the trial (i.e., Sample),
we would expect to capture early, sensory-based representations. By testing such a classifier
on every time point in the trial, we could determine if such a representation remains stable
throughout the trial, or if it deteriorates over time. Similarly, training a classifier with data
from a time point late in the delay-period (Late Delay) might capture a recoded
representation (e.g. verbal or numeric or clock-face), which would be expected to be absent
at the beginning of the trial and to strengthen over the course of the delay-period when we
look at the time point-by-time point decoding performance of that classifier. By limiting our
training data to a single time point during the trial, we hoped to maximize our ability to
resolve time point-by-time point changes, at the expense of lower signal-to-noise for the
classifier inputs.
Results from this analysis can be seen in Fig. 3A. The mean decoding accuracy for the
Sample classifier was significantly above chance (25 %, p < 0.05, permutation test)
throughout the entire delay period. Similar results were obtained with the Late Delay and
Probe classifiers. These results suggest that the memory representation remains relatively
stable and unchanging across the delay period. Decoding accuracies for the ITI classifier
were always near chance, which was expected given the absence of any stimulus-related
information for the classifier to learn (i.e., signal from 8 sec after the offset of the memory
probe would not be expected to carry information about the stimulus from the preceding
trial). As with the univariate analyses, all trials were included in the analyses. Follow-up
analyses using only correct trials produced qualitatively similar results.
To assess the specificity of the classification, the set of classifiers trained to discriminate
direction with data from direction-cued trials were also used to decode direction information
from speed-cued trials. (Fig. 3B). Classification with the Sample, Late Delay and Probe
classifiers was above chance for time points before the cue, when subjects needed to hold
both speed and direction information in memory, but fell to chance levels following the cue,
suggesting that subjects discarded direction information when it was no longer relevant to
the current trial.
Two features in the data confirm that successful Late Delay decoding of direction-cued trials
represents the sustained retention of stimulus information and does not reflect an artifact of
the slow recovery of the hemodynamic response, nor effects of motion adaptation. First, if
the results were purely driven by the residual hemodynamic response to the sample stimulus,
or to adaptation, we would expect to see similar decoding performance on both direction-
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cued and speed-cued trials, because the sample stimuli are identical across these two
conditions. Second, such "residual" effects would also result in successful decoding by the
ITI classifier, which was trained with data 10 seconds following the probe stimulus
(compared to 16 seconds following the sample for the Late Delay), which it clearly does not.
The whole-brain classification procedure was also applied to the stimulus dimension of
speed, using data from only speed-cued trials. Unlike direction, however, classifier
performance never exceeded chance for any time point during the trial. Because subjects
performed these trials at the same level of proficiency as direction-cued trials, we interpret
this null result to mean that the representation of speed, at least across the range used in this
experiment, may be carried out on too fine a spatial scale neurally to be discriminated with
our fMRI procedure. It is also possible that by collapsing across different directions when
classifying the speed trials we added too much noise to the signal to classify, given the close
relationship between speed and direction (Born and Bradley, 2005). Additionally, the use of
only three speeds may have encouraged a coding strategy that varied over time (e.g., verbal
labels that changed as the stimuli became more familiar to subjects). The remainder of the
Results and Discussion will focus on decoding direction information.
ROI-Constrained Classi cation
To test our first hypothesis—that elevated delay-period activity carries stimulus-specific
information—we repeated the classification procedure that we used with the whole brain
data, but applied it to only those voxels in the frontal or parietal cortices that showed
elevated delay-period activity as identified with the univariate analysis. As can be seen in
the average BOLD time series in Fig. 4A and 4B, each of these areas showed elevated
activity that was sustained throughout the delay period. However, decoding performance for
motion direction never differed from chance in either area, regardless of the time point used
to train the classifier (Fig. 4E and 4F). Therefore, we failed to find evidence that the
sustained, delay-period BOLD activity in these regions carried stimulus-related information;
the first hypothesis was not supported. To rule out the possibility that using such large ROIs
may have obscured the presence of stimulus-representation in smaller regions, we repeated
the ROI-classification with the smaller, more specific ROIs described in the Methods
section. Results in all smaller ROIs mirrored those of the larger regions: no evidence for
stimulus-related information was found in any of the regions.
To test our second hypothesis—that stimulus-specific information can be recovered from
subthreshold patterns of activity (i.e., activity whose signal intensity does not surpass a
statistical threshold in conventional univariate analysis)—we repeated the classification
procedure as above, limiting the training data to only voxels in medial occipital or lateral
occipital and temporal cortex that showed no evidence of elevated activity during the delay
period in the GLM. As can be seen in the average BOLD time series in Fig. 4C and 4D,
these regions showed large sample- and probe-evoked responses, as well as smaller cue-
evoked responses, but no sustained, elevated delay-period activity. Decoding performance
from these regions, however, was significantly above chance throughout the delay-period
(Fig. 4G and 4H).
Although these posterior regions did not show sustained delay-period activity at the group
level (Fig. 2B.), there were voxels in the individual-subject data of each subject that did. The
results of pattern classification did not change appreciably when these voxels were included
or excluded from the analyses. Additionally, when the classifiers were trained only on these
posterior delay-active voxels, in no subject was decoding performance sustained at above-
chance levels across the delay period. Overall, these findings were consistent with the
second hypothesis, that brain regions can carry stimulus-specific information in a sustained
manner despite the absence of sustained, above-baseline levels of activity.
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These results form a double dissociation, with frontal and parietal regions showing elevated,
sustained delay-period activity but no delay-period stimulus representation, and posterior
regions the converse. One possible concern about applying these results to our
understanding of WM storage, however, is that doing so requires the acceptance of the null
MVPA findings in frontal and parietal cortex. Might it be the case, for example, that these
regions are simply less amenable to MVPA (perhaps, e.g., because they represent
information at a finer grain of spatial detail than is measurable with our fMRI methods)? To
address this possibility, we trained a new set of classifiers on a different discrimination – cue
identity (i.e., whether the relevant stimulus dimension was direction or speed) - and repeated
the procedure with each of the four ROIs. As shown in Fig. 4I-L, the relevant trial-
dimension was decodable from each of the four ROIs. Importantly, for each this was only
true for the Late Delay and Probe time-point trained classifiers, and only for time points
following cue presentation. These results indicate that frontal and parietal regions are not
inherently "undecodeable" with our methods, and, thus, lend more credence to the
possibility that they did not represent stimulus-specific information during the delay period
of our WM task.
The aim of the present study was to test long-standing views about the relationship between
the short-term retention of information and sustained delay-period activity. Using an
information-based analysis approach with fMRI data collected during a delayed-recognition
task for visual motion, we tested two hypotheses: first, that sustained, elevated delay-period
activity carries stimulus-specific information; and second, that stimulus information can be
encoded in distributed patterns of subthreshold activity. To test the first hypothesis we
trained pattern classifiers with BOLD signal from frontal and parietal areas that showed
sustained, elevated delay-period activity. We failed to find evidence that these voxels carried
stimulus-specific information during the delay period. To test the second hypothesis, we
applied the same procedure to BOLD data from posterior regions that showed robust
responses to visual stimuli, but no elevated delay-period activity. The classifiers were
successfully able to decode the remembered direction throughout the delay period, providing
strong evidence in support of this hypothesis.
The first finding can be seen as a failure to support an enduring assumption in cognitive
neuroscience, albeit one that is increasingly being called into question (Curtis and
D'Esposito, 2003; Lebedev et al., 2004; Curtis and Lee, 2010; Lewis-Peacock and Postle,
2012). Although on its own it might be qualified as a null result, there are several factors
that must influence its interpretation. Most saliently, it is paired with a positive result using
the same method, and derived from statistically "subthreshold" voxels located in areas that
are active during the perception of the to-be-remembered information. Empirical evidence
thus shows that this method is sensitive. Indeed, although there remains some controversy
about the physiological and representational factors that underlie the patterns of activity that
correspond to different brain states (Freeman et al., 2011; Thompson et al., 2011), we are
not familiar with any suggestion that there may exist brain states to which MVPA is less
sensitive than traditional analysis of activation levels of individual voxels or groups of
voxels. To the contrary, the near-consensus view is that MVPA methods are more sensitive
than traditional activation-based analyses (Kriegeskorte et al., 2006; Norman et al., 2006;
Haynes, 2011; Lewis-Peacock and Postle, 2012; Jimura and Poldrack, 2012).
Further, although we cannot rule out the possibility that stimulus information might be
represented in frontoparietal cortex at either a spatial scale that is too fine to be detected
with our fMRI methods, or perhaps via a signal to which BOLD is relatively insensitive
(e.g., low-frequency oscillations in local field potentials), we did demonstrate that this is not
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a limitation for the decoding of trial-specific task instruction-related information. From this
perspective our results are consistent with, for example, the finding from monkeys that PFC
and posterior parietal cortex (PPC) represent the category to which a stimulus belongs
(Freedman and Assad, 2006; Swaminathan and Freedman, 2012). It is also worthy of note
that although MVPA has been applied successfully to sensory processing in topographically
organized cortex (e.g., the decoding of orientation (Harrison and Tong, 2009; Serences et al.,
2009)), it has also been successfully applied to "higher level" processing in polymodal
cortex. Thus, for example, MVPA has demonstrated contextual reinstatement during
episodic memory retrieval (Polyn et al., 2005), the recognition of individual faces
(Kriegeskorte et al., 2007), and neural correlates of free choice (Soon et al., 2008), all
entailing the decoding of information from polymodal temporal, parietal, and/or frontal
Consistent with our preferred interpretation of the null findings in frontal cortex are several
factors. First, there are the results from extracellular recording in monkeys performing a
similar task with similar stimuli, where no evidence for direction-selective persistent activity
was found in the PFC throughout the delay period (Zaksas and Pasternak, 2006; Hussar and
Pasternak, 2012). Second, a similar pattern to the MVPA results that we describe here has
been reported for STM for four categories of visual objects (Linden et al., 2012) and for
complex artificial visual stimuli (Christophel et al., Revision under review). Third, the fact
that STM can be intact despite lesions of PFC (D'Esposito and Postle, 1999; Tsujimoto and
Postle, 2012) is consistent with the failure to find physiological evidence for STM
representations in this region.
The frontoparietal network that has been a focus of this study is known to support the
endogenous control of attention (Corbetta and Shulman, 2002; Beck and Kastner, 2009;
Noudoost et al., 2010). Interestingly, one account of WM storage is that it is supported by
this same top-down mechanism (e.g., Armstrong et al., 2009; Curtis and D'Esposito, 2003;
Postle, 2011). From this perspective, the sustained delay-period activity observed in this
study may correspond to a control signal that does not vary with stimulus identity. Future
work would need to reconcile this possibility with the finding that multivariate patterns of
frontoparietal activity do discriminate between directions of motion during a sustained
attention task (Liu et al., 2011). In addition to specifically memory-related functions, many
other functions might be supported by sustained delay-period activity of frontal and parietal
regions. Because the frontal and parietal activity observed in the present study (Fig. 4)
resembles activity that has been reported in countless prior neuroimaging studies (Curtis and
D'Esposito, 2003), it may well be that it does not correspond to a stimulus-specific or even
task-specific function. More general demands that many cognitive tasks (including working
memory tasks) have in common include decision making (Curtis and Lee, 2010), prioritizing
certain task-relevant representations and/or processes over others (Miller and Cohen, 2001),
monitoring the environment to control the processing of potentially interfering exogenous
events (Chao and Knight, 1998; Postle, 2005), actively representing a "behavioral set"
(Woolgar et al., 2011), and monitoring behavior so as to prevent prepotent responses
(Knight and D'Esposito, 2003), including perseverative responses (Milner, 1963; Tsujimoto
and Postle, 2012). (Note that although the behavioral set account might be consistent with
the successful decoding of cue identity in frontal and parietal regions, this explanation does
not generalize to the first portion of the delay period.) This is, of course, an incomplete list.
One important question for future study is the nature of the mental codes with which
subjects represent motion information across the delay period. In the monkey, a
psychophysical study using backward masking provided evidence that the initial memory
trace is perceptually based, retaining a high-fidelity representation of the sample (including
such trial-irrelevant information as the local velocity of individual dots in the random-dot
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motion stimulus). This representation only endured few hundred milliseconds into the delay
period, however, perhaps because, in this study, the animals could predict the major features
of the impending memory probe (Zaksas et al., 2001). Although the BOLD signal did not
afford high temporal resolution in the present study, results with classifiers trained on
different portions of the trial suggested that the mnemonic representation is relatively stable.
We cannot know with certainty, however, whether this representation was primarily
perceptual, motoric, or categorical in nature, or perhaps some combination of these. Our
working assumption is that the mnemonic representation of direction was perceptually
based, because it is from visual regions that we were able to recover stimulus direction
information. Had subjects used, for example, a covert eye-movement strategy, we would
have expected to have been able to decode stimulus information from frontal and parietal
regions (Ikkai and Curtis, 2011). The same reasoning makes us skeptical that subjects
depended on a verbal strategy for remembering either direction or speed. We did not,
however, monitor eye movements, nor take steps to discourage covert speech.
The results presented here highlight the differing conclusions that can be drawn from
activation- vs. information-based analyses of the same data set. In so doing, they raise
questions about the longstanding belief that information retained during working memory is
stored via sustained delay-period activity, preferentially in frontal and parietal cortex.
Instead, the memory trace may be represented in patterns of "subthreshold" levels of activity
distributed across regions of low-level sensory cortex.
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Figure 1.
Behavioral task. Participants maintained the direction and speed of a sample motion
stimulus over a long delay-period. Midway through this delay period they were cued as to
the dimension on which they would be making an upcoming comparison, either direction or
speed. At the end of the delay period they were presented with a probe motion stimulus and
had to indicate with a button press whether it matched or did not match the sample stimulus
on the cued dimension.
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Figure 2.
Univariate GLM results. (A) Sample-evoked, and (B) Delay-related activity, as estimated
from a group-level GLM, thresholded at p < 0.05, FDR corrected, and displayed on a
representative subject's inflated surface. Note that images are for illustrative purposes only,
as all analyses were performed on single-subject data. Superimposed is an outline of MT+ as
defined by the localizer. Note for this region that it is robustly activated by the sample, but
that its activity does not differ from the baseline during the delay period. A qualitatively
similar pattern is observed in calcarine and pericalcarine cortex. LH, Left hemisphere; RH,
right hemisphere.
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MTV Video Music Awards 2014
MTV VMAs: 5 Things That Set It Apart
From pop star PDA to stage-crashing headliners, a by-the-numbers breakdown of MTV's wildest awards show
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Yeah, it wasn't as bad as I thought. I tried not to clench and things went pretty smoothly.
I was on top riding him and his friend walks in and watched for a minute before he realized what was going on
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the EMT asked how you broke your nose and you said, "you know, the usual wear and tear."
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I'm trying. I feel like we're trying to have sex with fruitcake. dry and boring.
mom had to come pick me up from the hotel. I crawled to her car. She told me the entire way home if I puked in it I was going to lick it up. Like high school all over again...
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Newtown Square
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I'll bet this will come as a wild surprise, but I've been using Corel X6 for the last four weeks and it is a complete lemon. Shocking I know.
Apparently, it's JUST ON MY COMPUTERS, but I can't open 75% of the files done in X5 and most times can't open any files actually saved in X6. It's reduculous. It just crashes.
It happens on all the computers at work, but my home computer runs it just fine. Figure that out.
I have sent crash logs to Corel and they are looking into it, but in the meantime we're simply using X5...with all IT'S bugs...
There are some crazy awesome new tools, but alas... I can't get the f'in thing to even run half the time.
Just sayin, in case you were going to run out and buy it right away. Wait for SP1 at least.Tags: None
HOw do you get the Adobe suites free for reviewing? I want in on that!!!
Keyare, as for the Corel issues... It's been a while, but I remember in the older versions (3-6) I used to have problems where I'd be working, then Corel would crash. When I restarted, my ENTIRE FILE was lost (Actual file was still there, but was blank when I opened it). The "work around"/fix was there was some folder hidden in the Corel folder that holds the temp data. I had to figure out/find the one associated with that file - based off date/time - then delete it. That only worked about 55% of the time, but I had nothing to lose. And like I said, it's been so many years since I used it, I couldn't even tell you where to find the folder... Good luck tho!Typos are very important to all written form. It gives the reader something to look for so they aren't distracted by the total lack of content in your writing.
- Randy K. Milholland
Originally posted by Kool View PostYou just have to run a fairly popular and well established online graphic design magazine. About 3 months before CS4 came out they flew me and a bunch of other "journalists" to San Jose for 3 days and let us play around with it.
So, is this what the GDF is considered by the industry? An online graphic design magazine? Or is there another secret life you lead, oh Kooliness?
Originally posted by Kool View PostYou just have to run a fairly popular and well established online graphic design magazine. About 3 months before CS4 came out they flew me and a bunch of other "journalists" to San Jose for 3 days and let us play around with it.
Originally posted by Bob View PostThat explains the difficulties I have had in finding a centerfold.
Thanks.Typos are very important to all written form. It gives the reader something to look for so they aren't distracted by the total lack of content in your writing.
- Randy K. Milholland
I'm quite new with using programs such as Corel Draw. I was intended to draw some lines for a general two-dimensional physics diagram, but as soon as I applied new objects, the previous moved away (changed their shape). I don't know if which Options must be modified.
For a better imagination I enclosed a snapshot:
View My Video
I would like to thank you in advance for your favourable response!


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Good values on homes are still available, as the number of homes listed for sale is greater than the number of homes being sold. Great deals can be found by determined buyers.
Not enough data to determine market type. Consult a local REALTOR® for up-to-date market summaries
Trend data coming soon.
Trend data coming soon.
For Sale: 25 | New: 2 | ||
$199,000 | N/A | Recently Sold: 34 | Reduced: 14 |
Average Home Price | Average Sold Price | Property Records: 2,183 | Foreclosed: N/A |
The average home price in Red Cross is $199,000. The average home price per square foot in Red Cross is $0 and about 2% of all homes in Red Cross sold in the last 6 months. For Red Cross home values, real estate prices, and city market trends, research the 2,183 property records or search our 34 recently sold or 25 homes for sale listings. The listings and properties in Red Cross are only a part of the 3,528,531 properties and 78,373 homes for sale in North Carolina. Because of this, the average home price and average home value of Red Cross also influence the average home price $193,895 and average sale price $227,446 of North Carolina. Listing counts, Red Cross home prices and home values in Red Cross are sourced daily from listing and property data on realtor.com®, which is the most up-to-date and accurate aggregation of real estate listings in the industry and includes approximately 800 regional MLSs and is the official website of the National Association of Realtors®.


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Welcome to the All Hazards ConsortiumThe All Hazards Consortium (AHC) is a state sanctioned non-profit organization focused on
expediting getting business back to business in support of community and economic resilience. The AHC includes thousands of stakeholders at all levels of government and the private sector, representing over 60+million citizens and a significant percentage of the nation's critical infrastructure. For more information on the AHC, please click here. Recent Announcements
AHC In the NewsHughes to Provide Data Services for All Hazards Consortium Published November 13, 2014 / Hughes Network Systems has signed up to provide data sharing services for the All Hazards Consortium to help disseminate real-time information to disaster managers, emergency response leaders and first responders in cooperation. Learn More... Press Release, 11/2014
Hughes, the All Hazards Consortium and the Multi-State Fleet Response Working Group Announce a Strategic Data Sharing Partnership. Learn more..... Hughes, the All Hazards Consortium and the Multi-State Fleet Response Working Group Announce a Strategic Data Sharing Partnership Lessons Learned from SuperStorm Sandy Response Activities to Aid in Future Disaster Preparedness and Response. Lean more...
Recent Products and PublicationsAnnual Report of the Fleet Response Working Group
This is the first Annual Report issued by the Working Group. It outlines for activities, exercises, partnerships and products produced in 2013. To view the full report, please click here. Post-Sandy Report from the 2013 Annual Meeting of the Multi-State Fleet Response Working Group
The report captures the participants, issues, discussions, lessons learned, best practices, current solutions, outcomes, opportunities and recommendations from the electric and fuel (gas/oil) sectors. To view the full report, please click here. |


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Greetings and please browse our site!
Never tried Hashing before ? All you need is a T-shirt, Trainers and most importantly... a good sense of Humour! For more about what Crapaud's & Hashers generally do see our About page. We will make you very welcome, do try out one of our Runs.
Read our Booklet about Crapaud history. More nonsense in our 25th Anniversary of Jersey Hashing Weekend Celebrations Chronicle, October 2011.
Runs every Sunday 10am from selected hostelries. See our Hareline for more details
Newcomers (Virgins) free for 4 Runs: Weekly run Subs Members £4.50, Non-Members £5.50, Tadpoles £3.
Our 1,335 Run: Sunday 1 March: Royal St Martin, park opposite Salle Publique for 10.00am start. Hare: Please Insert
2015 FRENCH BIKE BASH: You must book holiday for Friday 4 September 2015, due to ferry timings we depart early that morning. Hare's Tinky Winky, Fuzz & Twin Peaks guarantee will be in France and promise Virginal territory.
CRAPAUD'S 2016 SKI-ING TRIP: Next year our ski-ers are going really Off-Piss(te) to Canada in early March 2016. Hopefully visiting Whistler's Twin Peaks. But booking needs to be made before middle of March 2015. So if you are keen to glide down the Twin Peaks please contact Twin Peaks quick about signing up for a fabulous time!
Your first time as a Hare? Don't worry, use the instruction manual! (Updated Dec. 2011)
LAST RUN HANKY PANKY: Extreme Hashing: Virgins & Visitors galore this morning to see what Hashing in Jersey is really like courtesy of Hare Bagsofit who laid on a long, long Trail. Including loadsa Fields and Shiggy. Bagsofit warned us tie our laces tight and despite this a few trainers came off in the gloopy gunge. Jacko was punished for suggesting Pack should run our Hares full Trail (6.8 Miles Muff-Finder panted) along with running Virgins Alistair & Madelaine. Madelaine struggled so was persuaded to empty glass over her head. Early Birthday Down-Down's for McKinsley & Illegal. Frisco escaped being arraigned because his "sore thumb" could not raise glass above his elbow. On On.


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License & Identifications
A medical license is required for a doctor to practice medicine in a particular state. Requirements vary by state but most require, at a minimum, post-graduate training in the doctor's specific specialty. An NPI number is a national identifier unique to an individual health care provider and is managed by the Center for Medicare & Medicaid Services (CMS).
Learn more about Dr. Bob Nagano:
View the full profile to get information on:
- Qualifications
- What's important to you
View full profile
Patient Reviews
The overall average patient rating of Dr. Bob Nagano is Excellent.
Similar doctors nearby
- Additional Information
- Dr. Bob Hisao Nagano DDS is a male dentist and practices in Family Dentistry.
- Where does Dr. Bob H. Nagano practice?
- Dr. Bob Nagano has 1 office location.
Dr. Bob Nagano practices Family Dentistry near Stanton, CA.
See Stanton Dentists.


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Tokico HP Series shocks and struts are the choice of performance enthusiasts! With Tokico HP Series' unique piston design, you will soon realize--and feel--that not all shocks are created equal! The piston rods are hardened, chrome plated, and micro-polished for smooth operation. Their multi-stage, variable-aperture valve system features precise orifice control, offering flexibility and accuracy in their damping response. Plus, the oil lubricant is specially compounded to resist breakdown and minimize viscosity change. Precision construction of the double mandrel-drawn pressure tube and reduced friction of the polytetrafluoroethylene coated piston rod guide also contribute to their superior handling, stability, ride quality, and the longevity you will experience. Upgrade the performance of your vehicle--even if you've added lowering springs and larger, heavier wheels--with Tokico HP Series shocks and struts.
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Order this item and get free delivery and handling on your entire order! Offer excludes truck freight fees. Valid on orders shipped in the contiguous United States.
Shock, Strut, HP Series, for use on Acura®, Honda®, Front, Each
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Gordon Dixon
From Wikipedia, the free encyclopedia
(Redirected from Gordon Henry Dixon)
Gordon Henry Dixon, OC FRSC FRS (born 25 March 1930) is a Canadian biochemist, and professor at University of Calgary.[1] He won the 1980 Flavelle Medal.[2]
He lives in Victoria, British Columbia.
This biography of a Canadian academic is a stub. You can help Wikipedia by expanding it. |


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Venice Medical Center
Medical Dispensaries / West Los Angeles (638,172 hits)Reviews
Great service!!
Came here with a friend on a Sunday afternoon. Sign up was quick and easy. Except there was this portion which confused me, that asked for volunteer hours. But Dana who was servicing the front at the time was very helpful with all the questions i asked. She was very positive and presented excellent service.
The bud-tenders were attentive of the amount of people that were crowding in. And helped who was ahead of me pretty quickly. The menu had a great selection, and easily sorted out into categories. (so its easy to spot what you want!!) The prices for the concentrates were more than reasonable. I picked up a couple grams of some Vader Extracts shatter for $60... not bad at all~
FTP was pretty standard, i took a schmedium sized dab, and a free edible was in the bag.
overall the place was great,
quick sign up, great service, Great product!!
Love these guys!!
I came here for patient appreciation day which is the 15th of every month! This place knows all about customer service, I got offered a dab while I was still waiting in line! Then I got a huge deal on the wax I got and 2 more fat ass dabs!! Talk about getting fucking hooked up!!
Let's Get Medicated
This is my new favorite spot. Nate and the rest of the staff are very kind and gracious. I always leave happy when I visit VMC.
That Enail though!
Fresh Buds
They got some pretty fresh buds here and at great prices too.
Best Wax Deals!!! Waax Spot
Vader Extracts has some amazing wax cant beat it. If your looking for something a little heavier, I like Crown Extracts and West Coast Cures have a nice selection of a little heavier wax as well
I li ked this place a lot but e,very now I will check out;
another spot to see whats up. In two days I went to two different places mainly for edibles. wow what rude clerks. I believe the places were "related", same stock. both places the tenders try to sell me a 20 buck cookie. One place made me wait while they got high and then the tender couldn't talk. Learn my lesson, the grass isn't greener on the other side. VMC rocks
1 personthought this review was helpful!
Powdery mildew, do not trust this place. Asked for the stickiest and they gave us King Louis with powdery mildew. All negative reviews for this place get deleted. Their GSC is crap. Calyx are humungous, they are supposed to be tiny.
Real PHire
evryting looks so nice when i heard about here like 2 wks ago. danky dank,GOTTA check this place out if u wanna c some real phire
Best in concentrates
This shops dope AF bringing my girlfriend in to check out the wax the concentrates here are always worth the long drive here definately getting your money's worth
Come see the Kings of wax
Zack is Back!!
Good to see you Zack! Nate set me up with some Girl Scout Cookies and Some White Fire Concentrates...UNREAL See you guys soon
First-Time Patients
* Every Friday is 45 CAP & discounted meds!!
Available Here
Hours & Info
Culver City, CA, 90232


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All What's New
- Today
- Past 7 Days
- Past Month
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- Specific Date Range
- Annual Report (693)
- Brief (1202)
- Directory (5)
- Africa (1630)
- East Asia and Pacific (1227)
- Europe and Central Asia (1176)
- Date
Maize price volatility : does market remoteness matter ?
This paper addresses the role of market remoteness in explaining maize price volatility in Burkina Faso. A model of price formation is introduced to demonstrate for... Show More +
MENA quarterly economic brief : plunging oil prices
In the three months since most observers, including the World Bank, issued their last forecasts, the Middle East and North Africa (MENA) Region has changed substant... Show More +
Empowering cities : good for growth ? evidence from China
This paper utilizes a countrywide, county-to-city upgrade in the 1990s to identify whether extending the powers of urban local governments leads to better firm outc... Show More +
The distributional impact of fiscal policy in South Africa
This paper uses the 2010/11 Income and Expenditure Survey for South Africa to analyze the progressivity of the main tax and social spending programs and quantify th... Show More +
Supporting women's agro-enterprises in Africa with ICT : a feasibility study in Zambia and Kenya
A new generation of information and communication technologies (ICTs) is finding a small foothold among poor, small-scale farmers in developing countries. Even so, ... Show More +
Improving environmental sustainability in road projects
The focus of this document is to provide a wide range of ideas and options to improve the inclusion of environmental sustainability throughout the road transportati... Show More +
R&D returns, spillovers, and firm incentives : evidence from China
This paper uses a new data set of 12,000 firms in China to estimate the returns to research and development investment and its spillover effects, and investigates h... Show More +
Clean air and healthy lungs : enhancing the World Bank's approach to air quality management
This report specifically deals with air pollution, which was reported, by the World Health Organization (WHO), as the single largest environmental health risk globa... Show More +
Palestinian Reform and Development Plan - Trust Fund (PRDP-TF) : quarterly review (July to September 2014)
The Palestinian Authoritys (PA) fiscal situation remains difficult and the latest conflict in Gaza has placed further pressure on an already tight budget. This sho... Show More +
Philippine economic update : making growth work for the poor
In the third quarter of 2014 (Q3), the Philippine economy expanded by 5.3 percent its slowest pace in 11 quarters. Growth slowed down due to the contraction of gove... Show More +
Guatemala - Elements of a transport and logistics strategy
This document has been produced by the World Bank to support the Government of Guatemala as it improves its transport and logistics sector management in pursuit of ... Show More +
Papua New Guinea - Social economic empowerment for women in mining and petroleum areas : improving livelihoods in extractives communities
The extractive industries sector has been vital to the local economy of Papua New Guinea for over 20 years. Extractives have contributed substantially to government... Show More +
Papua New Guinea Energy Sector Development Project
The objectives of the Energy Sector Development Project are, through technical assistance, to strengthen the policy development and strategic framework for renewabl... Show More +
OECS ports : an efficiency and performance assessment
Handling charges in Caribbean ports are two to three times higher than in similar ports in other regions of the world. In some cases, it costs significantly less to... Show More +
Connectivity for Caribbean countries : an initial assessment
Every discussion of the Caribbean states considers their characteristics as sea-locked countries, small economies, highly vulnerable to natural disasters, and a geo... Show More +
Integrating variable renewable energy into power system operations
Wind and solar energy is a fast-growing share of the global energy mix. But integrating them into power-system operations requires significant adaptations to compen... Show More +
Scaling up access to electricity : pay-as-you-go plans in off-grid energy services
Although the payment models offered by off-grid energy companies are less flexible than those implemented with great success by mobile telephone companies, they may... Show More +
Vulnerability to malnutrition in the West African Sahel
This study estimates marginal increase in malnutrition for children ages 1-3 years from exposure to an extreme shock in the West African Sahel. The study uses knowl... Show More +
Sustainability of solar electricity : the role of endogenous resource substitution and market mediated responses
This study seeks to understand how materials scarcity and competition from alternative uses affects the potential for widespread deployment of solar electricity in ... Show More +
Gone with the storm: rainfall shocks and household well-being in Guatemala
This paper investigates the causal consequences of Tropical Storm Agatha (2010) -- the strongest tropical storm ever to strike Guatemala since rainfall records have... Show More +


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Library Branch
Book Clubs & Writers' Groups
An hour long book talk and get together
Tue Mar 10
Tue Apr 14
Tue May 12
Tue Jun 09
Afternoon Book Club meets at 2:00 p.m., the fourth Friday of every month and is open to all interested book lovers in the community. For more information or to register visit the branch or call 416-396-8890.
Fri Feb 27
Fri Mar 27
Fri Apr 24
Fri May 22
Fri Jun 26
Share and improve your memoir writing skills with your writing group.
Tue Mar 17
Tue Apr 21
Tue May 19
Tue Jun 16
If you enjoy reading a range of literature & talking to others about books, this group is for you. Meetings start at 7 p.m....
Join us for stimulating conversation. You and your fellow book club members decide in advance which books you want to read. New members are always welcome.
Tue Mar 24
Tue Apr 14
Tue May 19
Tue Jun 16
Meets on alternate Saturdays: Starting at 10:30 a.m....
Sat Mar 07
Sat Mar 21
Sat Apr 04
Sat Apr 18
Sat May 02
Join the BF Kids' Book Club for children ages 8 to 12. Learn about new books, share your favourites, and play fun games and activities! Register in person or by calling 416-395-5440.
Mon Mar 30
Mon Apr 27
Mon May 25
Join Gerrard/Ashdale's book club to read, talk and play a game related to the book of the month! For ages 8 to 12 years....
Wed Mar 25
Wed Apr 22
Wed May 20
Wed Jun 24
Join us for stimulating conversation. You and your fellow book club members decide in advance which books you want to read. New members are always welcome.
Thu Mar 26
Thu Apr 16
Thu May 21
Thu Jun 18
Calling all book lovers! Share your love of books by attending Barbara Frum's Tuesday Book Club where you will get a chance to meet new friends and participate in a lively discussion. Members meet once every month at 6:30-7:3...
Tue Mar 24
Tue Apr 21
Tue May 19
Tue Jun 23


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Energy XXI adds to Gulf of Mexico assets
Energy XXI Ltd. has agreed to acquire certain oil and gas interests from MitEnergy Upstream LLC in a cash transaction worth $283 million.
The deal includes 30 fields currently producing 8,000 net barrels of oil equivalent per day, about 77 percent of which is oil, and 80 percent of which is already operated by Energy XXI (NYSE: EXXI). Offshore leases included in the purchase total nearly 33,000 net acres.
The deal is expected to close in early 2010.
Incorporated in Bermuda, Energy XXI is an exploration and production company with operating headquarters in Houston.
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