Download 10-21-09

Day 5
10:01
Roee Gilron, Brandeis; First Impressions. What determines if we remember a
first impression? One’s state? How one diagnoses the person? Behavioral studies
have focused on a single action and a single actor (Uleman 2008). Imaging studies
(Mitchell 2006, Harvey 2007, Schiller 2009) used multiple actions from a single
actor. Is there a social memory system? The HP doesn’t seem to be involved; the
dmPFC seems to be. This study asked participants either about the targets’
impressions or semantic information, given pos/neg (diagnostic) or neutral
sentences. Diagnostic sentenced targets were remembered better. Brain activity was
remembered in encoding stage based on which targets were remembered
successfully. The dmPFC and aCC emerged as significantly activated regions. The left
inferior frontal love was found larger for semantic memory than implicit memory.
The HP was more active in neutral memory rather than diagnostic memory. ACC
involved in incidental impression formation, but not intentional impression
formation. HP engagement supports incidental but not intentional impression
formation.
Donna Bridge, Northwestern; social; power mediates math. There is a neural
basis of social hierarchy (Zink 2008, March 2009, Freeman 2009, Chiao 2009). Social
power is defined as the ability to control outcomes of situations, particularly
allocation of resources. Social power can be primed by asking to write an essay
about when they encountered social power. High power reduces susceptibility to
interference (Smith 2008) and enhances global attentional processing (Guinote
2006). Low power emphasizes analytic processing strategy, focusing on details; and
it reduces their ability to filter extraneous information. (It may come from a fear
that others are manipiulating them.) Abstract and concrete math skills can be
dissociated, and abstract math predicts math achievement. The two conditions in
this experiment involved exact calculation (3+4= 6 or 7?) or approximate
calculation (3+4= 6 or 9?). Exact involves rote memory retrieval, learning does not
generalize, and involves left IFG. How does social power affect neural mechanisms
underlying math mechanism? Power may distinguish strategies used. High power
may rely more on IPS; low power may use lIFG. Half of the participants were primed
to high-power, the other half low. Surveys on mood, ACT, math ability, etc. showed
no differences. High-power participants were better at approximate, approaching
significance. Exact recruited lIFG and angular gyrus. Approximate exhibited IPS and
SPL. Low-power group recruited lIFG more for approximate than exact. Low-power
participants recruited dACC more for approximate calculations relative to exact.
Marina Pavlova, Tübingen, Neuromagnetic cortical correlates to social
communication. Right temporal has been described as “social brain area.” And yet,
preschoolers consistently describe cartoon of abstract shapes as social interaction.
ASDers are impaired on this social interaction, providing only physical
interpretations. ASDers have reduced connectivity to STS, reduced structural STS. In
these activities as well as wireframe animations, rSTS and right fusiform face area
are activated. Gamma activity has been shown to underlie intact brain
communication (Womelsdorf 2007), particularly social communication.
Exzperiment used shapes “caressing” and “kissing” (as commonly described by
viewers). rSTS and right PTJ were activated, unsurprisingly. The study also looked at
gender differences. Are these differences natural or sociocultural? Females are
generally better than boys, except for faces such as anger. There were no gender
differences for region activations across averages. In left medial prefrontal area,
females showed a peak much earlier than in males. This area is involved in
perceptual decision making. Females anticipate social interaction, whereas males
have to pay high prices for their errors. Future studies may wish to study these
differences in ASDs.
12:42
Turns out, the NAcc core is involved in acting on reward-predicting cues, and
the shell is involved in not acting on non-predictive cues. The neuronal firing
activities of the two regions looks the same, although the firing of individual
neurons on the core can be predicted by the reward-predictor, whereas those in the
shell merely act due to lever pressing.
The OFC is involved in mediating reward, and delaying rewards for the longterm. Animals tend to prefer short-term, immediate rewards over long-term ones.
The preference for long-term rewards is mediated by the OFC.
Deactivating the prelimbic vmPFC with muscimol and balcofen does not
decrease food seeking in hungry rats under a FR1 schedule, but it does under a
progressive ratio schedule.
13:32
Executive control nanosymposia. I’ve arrived late, so my notes on the earliest
few presentations are nonexistent.
Keliris GA, V1 in executive control. Binocular rivalry is interesting because
input remains the same but perception fluctuates: Two images are presented, one in
each eye; subjects perceive the image in the center of the field as varying. V1 is of
interest because it is the cornerstone of the visual system and is the first stage of
binocular interaction; that is, the first place where information from the two regions
interacts. Previous studies (Logotbetis, 1998) suggests that the competition is
happening in the temporal lobe, but primate (incl. humans) implicates activity in V1
activity in this process, and fMRI studies implicating V1 in visual field dominance. Is
this competition between low-level eye channels, or higher stimulus
representations? They used the technique of binocular flash suppression, which
involves an animal viewing two screens, with both eyes centered on the center of
their respective screens, with competingly oriented stimuli. Single cell studies in
primates showed 20% of neurons showing perceptual modulations in the twostimulus conditions. Gamma wave activity mimics the behavior of single cells. Cells
were then categorized according to which orientation of stimuli they prefer, and
which ocularity (left/right eye) they prefer. All cells were evenly distributed,
concentrated most highly around the origin; same goes for those cells that showed
visual disturbances. Cells were categorized according to whether they’re modulated
by ocularity or orientation, or both. The activity of these cells can predict perceived
orientation and eye-of-origin according to their sensory preferences.
Shi-Chieh Lin, Duke/NIA. Attention enhances PFC ERP mediated by non-ACh
basal forebrain neurons. Basal forebrain is center of ACh-ergin neurons that project
throughout cortex, important for to-down attention, cortical activity/plasticity, and
arousal states. Yet, the majority of basal forebrain output is GABAergic, and to a
somewhat lesser degree, glutamatergic. (These two combined make up 2/3 of the
output.) These latter neurons innervate cortical interneurons, perhaps disinhibiting
cortex. How do we identify these non-ACh-ergic output? ACh phenotype of arousal
was used to isolate neurons in rats. Once these neurons were isolated, rats were
given a go/no-go task to see if these non-ACh-ergic neurons were involved in
attention. Multimodal, rewarding and non-rewarding, and motor- and passivityincentivizing cues were use; the only consistent property was salient. These
neurons fired in response to the salient stimuli, and only after the conditioning.
(Extinction eliminates this firing.) Next, they sought to relate the firing to
performance. All-or-none burst firing, typical of the neuron population, predicted
successful tone detection. This pattern is consistent in all neurons that show the
bursting response. Next experiments involved ERPs in humans, involving an oddball
task, a commonly us4ed attention task in humans. Cortical ERP bursting should be
correlated with BF activity. Target stimuli were seen to recruit great bursting, and it
was correlated nicely with cortical firing. Even baseline, non-target firing was
correlated in both regions. This test was performed multimodally. A good analogy
for the BF activity in top-down attention is as a signal amplifier for those stimuli
which are salient.
E. Procyk, Bron (Fr); PFC in dynamic behavior. Relation between aCC and
lateral PFC. ACC is involved with encoding & adapting action values to bias decisions
and detecting/evaluating action outcomes/feedbacks; lPFC is involved in
implementing cognitive control. ACC and LPFC are active (monitoring/controlling?)
during adaptive behaviors. A test was devised in which a monkey had to search for a
target, repeat the behavior directed at the correct target, and then transit to
searching for the next correct target after a signal to change. Average region activity
was recorded with electric-recording plates on the ROIs. In the ACC, incorrect and
the initial correct responses were higher than repeated correct responses, and the
incorrect condition produced a higher peak and greater latency than the first correct
response. In the LPFC, the incorrect responses produced greater activation than
either of the correct responses. LPF was more involved in searching. Signal to
chance resulted in above-baseline activity before the feedback in ACC and LPFC. ACC
incorrect responses shows activity before any PFC activity. ACC, therefore, was the
immediate region to react to the change; the LPFC acted mostly after the signals
indicated a need to change response.
MaryAnn Noonan, Oxford; mOFC in relative reward comparisons in the
Macaque. It is more challenging to select options when their rewards are more
similar than when they’re more difference. It’s even more difficult when there are
multiple options. mOFC damage influences how much the third option influences
the choice in options. Four monkeys were lesioned in the mOFC. This experiment
will be compared to monkeys damaged in the lOFC from previous experiments. The
experiments involved selecting from three stimuli on a screen, each of which having
varying probabilities for reward. The second-best option (V2) had its probability for
reward vary between trials. When only given two options, and when the difference
is large, the monkeys had no problem figuring out which to choose, same when the
difference was moderate. When it was small, it was a struggle to determine. lOFC
lesioned monkeys had an opposite trend, performing worst when the differences
were greatest. After, in a difference experiment, reward schedules fluctuated
continually throughout. (I’m not sure how this experiment works; it’s not clear to
me and went by too quickly. It involves too much abstract math and statistics too
quickly for me to understand it.) It was shown (somehow) that including a third
option made post-op animals choose the best option less frequently, unlike pre-op.
(Look up the “independence axiom.” Controls follow this principle; others do not.)
Andrew Bell, probability. How does prior probability bias choice? Inferior
temporal cortex represents end stage of higher order visual processing.How/if do
priors (prior probabilities) influence IT? Is IT merely sensory? If so, we would only
expect its role to be limited to one stimulus. Monkeys were presented cues (with
noise), then they had to saccade to the previously displayed stimulus. Single
neurons were selected, and compared for conditions when cues were 100%, 75%,
and 25% faces. The response during correct responses was proportionate to the
probability of facial appearance. When the cues were 100% faces and the monkey
chose incorrectly, though, the signal was reduced. When the cue was 50% faces, the
same trend was present but reduced. (Possible confounds are using faces, given the
STS’s role; also, it’s unsure how much this extends to other modalities.)