House of Mind

"Biology gives you a brain. Life turns it into a mind" - Jeffrey Eugenides

  • 12th December
    2010
  • 12
During my last day at SfN 2010, I ran into this poster. The title instantly reminded me of Emir, my grad school friend notorious for his commitment to gaming. His game of choice? Yup, you guessed it: WoW.  As a consequence of his hard gaming hours, Emir’s brain has developed somewhat differently. Read on for a structural MRI study on the neuroanatomical differences in action-video game experts (AVGE). Neuroanatomy of Action-Video Game Experts (Tanaka et. al): AVGE have distinct rain-structure than non-experts because playing AVGs is thought to modify and improve some cognitive functions. Tanaka and others led a study that compared brain structures of AVGE with those of non-experts by using voxel-based morphometry (VBM), a neuroimaging technique that employs statistics to identify anatomical brain differences between groups. These differences can then be used to infer presence of atrophy or tissue expansion. The subjects considered AVGE had a mean video gaming experience of 17 years, at least 3 hours a day. These AVGE subjects where further divided by game type: fighting VGE or shooter VGE. Gray matter volume differences between AVGE experts (fighting or shooter) and controls were identified through VBM. Gray matter is an integral component of the nervous system which consists of neuronal cell bodies, neuropil (dendrites + axons), and glia cells. White matter on the other hand, is composed mostly of the myelinated axonal tracts.  Fighting VGE: Gray matter volume of extrastriate body area (EBA) in the occipital cortex, an area that has been implicated in the perception of body parts,  and right inferior parietal cortex, which integrates input from differen sensory modalities were significantly larger in fighting VGE compared to controls.  Shooter VGE: Gray matter in visual cortex, particularly the cuneus (a basic visual processing area), significantly larger compared to controls.  The study found that in AVGE brain areas related to visual perception and attention rather than the speculated motor control and decision-making areas exhibited statistically significant structural change. 

During my last day at SfN 2010, I ran into this poster. The title instantly reminded me of Emir, my grad school friend notorious for his commitment to gaming. His game of choice? Yup, you guessed it: WoW. 

As a consequence of his hard gaming hours, Emir’s brain has developed somewhat differently. Read on for a structural MRI study on the neuroanatomical differences in action-video game experts (AVGE).

Neuroanatomy of Action-Video Game Experts (Tanaka et. al):

AVGE have distinct rain-structure than non-experts because playing AVGs is thought to modify and improve some cognitive functions. Tanaka and others led a study that compared brain structures of AVGE with those of non-experts by using voxel-based morphometry (VBM), a neuroimaging technique that employs statistics to identify anatomical brain differences between groups. These differences can then be used to infer presence of atrophy or tissue expansion.

The subjects considered AVGE had a mean video gaming experience of 17 years, at least 3 hours a day. These AVGE subjects where further divided by game type: fighting VGE or shooter VGE. Gray matter volume differences between AVGE experts (fighting or shooter) and controls were identified through VBM. Gray matter is an integral component of the nervous system which consists of neuronal cell bodies, neuropil (dendrites + axons), and glia cells. White matter on the other hand, is composed mostly of the myelinated axonal tracts. 

  • Fighting VGE: Gray matter volume of extrastriate body area (EBA) in the occipital cortex, an area that has been implicated in the perception of body parts,  and right inferior parietal cortex, which integrates input from differen sensory modalities were significantly larger in fighting VGE compared to controls. 
  • Shooter VGE: Gray matter in visual cortex, particularly the cuneus (a basic visual processing area), significantly larger compared to controls. 

The study found that in AVGE brain areas related to visual perception and attention rather than the speculated motor control and decision-making areas exhibited statistically significant structural change. 

  • 24th November
    2010
  • 24
Hi. Enjoy your blog. Could you please pass along the link to the research you referenced in this post: Want vs. Should: Neural and behavioral effects of affect and cognition on decisions about material goods (Preston)

jsadlowe@gmail.com

Thanks!

Asked by: jonathansadlowe

I referenced to research that is unpublished but was presented at SfN this year. I’m supposed to get a copy of the poster from the author soon, but I haven’t. The best I can do know is copy/paste the author abstract from the SfN meeting planner. If you are not a member, you cannot access the link. 

Author Abstract: S.D. Preston. Want vs. Should: Neural and behavioral effects of affect and cognition on decisions about material goods. 2010 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience, 2010. Online. 

Research across species and domains suggests a common proximate, neural mechanism for making decisions about resources. Prior experiments on food storing in rodents, as well as human studies of compulsive hoarding, shopping, and gambling implicates the mesolimbocortical system, particularly the nucleus accumbens (NAcc) and orbital frontal cortex (OFC). Our own work confirms that this system is implicated in decisions to acquire as well as discard material goods, whether for personal use or monetary profit. This suggests that this system is more generally engaged by consumption decisions regardless of the frame. However, the degree of engagement of various regions does shift with the frame of the decision, as does the type of items subjects prefer. Personal decisions activate the self-referential, default midline systems more while decisions for financial benefit activate more lateral, cognitive control regions associated with comparing and calculating the value of items. In addition, using more natural and impulsive response formats causes subjects to highlight more immediately rewarding items like food and small change while more comparative and reflective response formats cause subjects to highlight items that one “should” have, but are less inherently rewarding. Demonstrating for the first time that animal and human hoarding are related by more than just a metaphor, the degree of NAcc activation in our task also scales with participants’ trait tendencies for human compulsive hoarding (particularly trouble parting with goods for emotional reasons). Additional work in our lab confirms that acquisitive tendencies are normally distributed in the population and are particularly associated with underlying differences in anxiety, which fuels the more deliberative system to emphasize the future utility of items that are not inherently rewarding. This research is consistent with prior work in rodents, monkeys, and humans, but additionally specifies how intrinsic, natural or pharmacological rewards differ from those associated with goods that are only conceptually consumed, but nonetheless motivate people to acquire them and exhibit features like addictions to drugs of abuse. Research on material goods is critical to understand a process that humans engage in daily, which is critical to our economy, our quality of life, and the environment.

Perhaps a search would yield extra results?

  • 23rd November
    2010
  • 23

Want vs. Should: Neural and behavioral effects of affect and cognition on decisions about material goods (Preston)

What brain areas are involved in deciding what we want to keep, what we can discard, what has meaning for us, and what has monetary value? 

A study carried out by Preston set out to explore the neuroanatomical substrates for these decisions by performing an fMRI task in which subjects made force-decisions between everyday goods. 

Before that, let’s familiarize ourselves with the term acquisitiveness, which is characterized by a strong desire to possess, gain or retain. Acquisitiveness is a trait that may be beneficial for heatlh, quality of life, and the environment. 

Findings

Personal decisions: According to Preston, “personal decisions activate the self-referential, default midline systems more while decisions for financial benefit activate more lateral, cognitive control regions associated with comparing and calculating the value of items.” Because these decisions are of an intuitive and affective nature, they engage affective and self-relevant regions like the orbitofrontal cortex, right angular gyrus, right middle temporal gyrus (MTG) and others. These decision are marked by increased activity in the medial prefrontal cortex (mPFC) and the anterior cingulate cortex (ACC), a self-processing area. 

Monetary decisions: are controlled and economical. They involve the right insula (value-judgement area), the dorsolateral prefrontal cortex (dLPFC), an evaluative area, and Broca’s area (analysis and planning).

Acquisition decisions: act like a hedonic (pleasure) signal are marked by an increase in desirability and engage the medial orbitofrontal cortex (mOFC) and nucleus accumbens (reward area) engagement. Decisions in which reward may be acquired are also related to associated with mesolimbocortical (MLC) regions. 

Discarding decisions: have elements of additional control and evaluation. Individuals usually think in utilitarian terms to establish preference and possessiveness has been shown to increase an object’s desirability. These are taken in basis of monetary value and involves the insula and the ACC.

  • All decision types (personal, monetary, acquire, discard) engage the mPFC. 
  • Acquisitiveness involves both acquisition and failure to discard.
  • Acquisitiveness entails incentive salience (motivational, wanting attribute due to the brain’s prediction for reward) for even mundane, utilitarian items. 
  • Hoarding behaviors are associated with the OFC. 


  • 17th November
    2010
  • 17
Considering I’ve been suffering from lack of sleep lately, a post about sleep and cognitive performance seems appropriate. I visited this poster on my last day at SfN10 and I finally got around to blogging about it. So here it goes… Sleep is thought to benefit decision-making and creativity as well as aid in problem-solving, consolidation of memory and transitive relationships. To test the effect of sleep on cognitive performance, Karmakar and others assigned experimental subjects to one of two different sleep sessions and conducted a cognitive task after the 12-hour period. Both groups had 12 hour sessions, but one group had 12 hours (sleep time included, from PM-AM) before the test while the other had 12 hours awake (AM-OM) before the test. For example, the 12 hour session of the sleep group were from 8PM to 8AM and then they went to take the test.  Results: 1. Sleep improves memory recall.  2. Sleep increases accuracy of attribute recall.  3. Sleep decreased the perception of decision quality and the time of day did not account for differences in recall or perceived decision quality. (Individuals who slept before the exam had less confidence and were less satisfied with their choices.) 4. Sleep benefits recall of positive information and hinders recall of negative information. Author Abstract (Karmarkar et. al): Impact of Sleep on Attribute Recall and Choice Satisfaction A wealth of recent studies has illustrated a role of sleep in memory but also many other cognitive processes such as problem-solving and creativity. While sleep deprivation has been shown to diminish decision-making, to date, studies have failed to directly investigate the impact of sleep on decision-making or choice. Yet, we often follow the wisdom that “sleeping on it” is beneficial to decisions. Thus, we examined whether periods of sleep influence recall for information pertaining to a decision as well as subjective perceptions of decision quality. Across studies, participants attended two experimental sessions separated by 12 hrs, either spent awake (AM-PM) or containing sleep (PM-AM). All studies were incentive compatible. During the first session, participants were informed that their selection from a choice set would be honored if they were chosen in a later random drawing. Participants viewed several positive and negative attributes relating to each of four commonly used items (laptop messenger satchels). Following an unrelated filler task, recall was assessed and participants rated the valence of each remembered attribute. In the second session, recall was tested again in a similar manner. After this, participants then indicated their preferred item from the choice set and rated the ease of this decision process, their confidence and their satisfaction with their choice. Overall, sleep significantly benefited attribute recall. Individuals in the PM-AM group showed an increase in responses, while those in the AM-PM group showed a decrease. These results applied to the total attributes recalled (inclusive of errors) as well as the accurate attributes only. Data from subsequent experiments with balanced numbers of positive and negative attributes suggest that the differences between groups may be due to improved memory for positive compared to negative attributes after sleep. Notably, despite the boost in their knowledgeability, PM-AM participants found the choice process more difficult and were less confident and less satisfied with their decision. These findings do not appear to be dependent on time of day. Single-session control groups, tested in the AM or PM, revealed no differences in baseline recall performance or perceptions of decision quality. Emerging data suggest that single item (yes/no) choices also result in less satisfaction after “sleeping on” decision-relevant information. Thus our results suggest that sleep may have some negative consequences for decision-making, decreasing decision satisfaction, despite improving knowledgeability about the choice set.

Considering I’ve been suffering from lack of sleep lately, a post about sleep and cognitive performance seems appropriate. I visited this poster on my last day at SfN10 and I finally got around to blogging about it. So here it goes…

Sleep is thought to benefit decision-making and creativity as well as aid in problem-solving, consolidation of memory and transitive relationships. To test the effect of sleep on cognitive performance, Karmakar and others assigned experimental subjects to one of two different sleep sessions and conducted a cognitive task after the 12-hour period. Both groups had 12 hour sessions, but one group had 12 hours (sleep time included, from PM-AM) before the test while the other had 12 hours awake (AM-OM) before the test. For example, the 12 hour session of the sleep group were from 8PM to 8AM and then they went to take the test. 

Results:

1. Sleep improves memory recall. 

2. Sleep increases accuracy of attribute recall. 

3. Sleep decreased the perception of decision quality and the time of day did not account for differences in recall or perceived decision quality. (Individuals who slept before the exam had less confidence and were less satisfied with their choices.)

4. Sleep benefits recall of positive information and hinders recall of negative information.

Author Abstract (Karmarkar et. al): Impact of Sleep on Attribute Recall and Choice Satisfaction

A wealth of recent studies has illustrated a role of sleep in memory but also many other cognitive processes such as problem-solving and creativity. While sleep deprivation has been shown to diminish decision-making, to date, studies have failed to directly investigate the impact of sleep on decision-making or choice. Yet, we often follow the wisdom that “sleeping on it” is beneficial to decisions. Thus, we examined whether periods of sleep influence recall for information pertaining to a decision as well as subjective perceptions of decision quality.

Across studies, participants attended two experimental sessions separated by 12 hrs, either spent awake (AM-PM) or containing sleep (PM-AM). All studies were incentive compatible. During the first session, participants were informed that their selection from a choice set would be honored if they were chosen in a later random drawing. Participants viewed several positive and negative attributes relating to each of four commonly used items (laptop messenger satchels). Following an unrelated filler task, recall was assessed and participants rated the valence of each remembered attribute. In the second session, recall was tested again in a similar manner. After this, participants then indicated their preferred item from the choice set and rated the ease of this decision process, their confidence and their satisfaction with their choice.

Overall, sleep significantly benefited attribute recall. Individuals in the PM-AM group showed an increase in responses, while those in the AM-PM group showed a decrease. These results applied to the total attributes recalled (inclusive of errors) as well as the accurate attributes only. Data from subsequent experiments with balanced numbers of positive and negative attributes suggest that the differences between groups may be due to improved memory for positive compared to negative attributes after sleep. Notably, despite the boost in their knowledgeability, PM-AM participants found the choice process more difficult and were less confident and less satisfied with their decision. These findings do not appear to be dependent on time of day. Single-session control groups, tested in the AM or PM, revealed no differences in baseline recall performance or perceptions of decision quality. Emerging data suggest that single item (yes/no) choices also result in less satisfaction after “sleeping on” decision-relevant information. Thus our results suggest that sleep may have some negative consequences for decision-making, decreasing decision satisfaction, despite improving knowledgeability about the choice set.

  • 17th November
    2010
  • 17

An opiate addiction switching mechanism dependent on D1/D2 receptor transmission (Lintas)

In short: 

  • The ventral tegmental area (VTA) and the basolateral amygdala (BLA) have long been regarded as key components in the brain reward circuit.
  • Chronic opiate administration switches the functional role of intra-BLA dopamine (DA) transmission from a D1-dependent substrate to a D2-dependent substrates.
  • This D1/D2 opiate reward switch in the BLA can directly modulate opiate reward information from the VTA. Furthermore, the DA reward processing occurs in the nucleus accumbens shell (not core) 

Author Abstract (Lintas, et. al) : Transmission through dopamine D1 versus D2 receptors in the basolateral amygdala represents an opiate addiction switching mechanism controlling opiate memory encoding in the drug naïve versus dependent state

The basolateral nucleus of the amygdala (BLA) receives innervation from dopaminergic fibers, and dopamine (DA) D1 and D2 receptors are expressed in this region. BLA sends excitatory afferents to the nucleus accumbens (NAcc), to both shell and core regions. The NAcore and NAshell are both implicated in the processing of various associative reward stimuli. However, the precise role of D1 versus D2 receptor transmission in the processing of associative, opiate-related reward learning is not presently understood. Using a combination of in vivo single unit extracellular recording in the NAcc combined with behavioural pharmacology studies, we have identified a double dissociation in the functional role of DA D1 versus D2 receptor transmission in the BLA, as a function of opiate exposure state: thus, in previously opiate-naïve rats, blockade of intra-BLA D1, but not D2, receptor transmission blocks the rewarding effects of morphine (5mg/kg;i.p.) measured in an unbiased conditioned place preference (CPP) procedure. In direct contrast, in rats made opiate dependent and in a state of withdrawal, intra-BLA D2, but not D1 receptor blockade completely blocks opiate reward encoding. We find the same double dissociation with intra-BLA D1/D2 activation: in opiate-naïve rats, pharmacological activation of intra-BLA D1 (but not D2) receptors strongly potentiates sub-threshold morphine (0.05mg/kg;i.p.) reward encoding while activation of D2 receptors (but not D1 receptors) potentiates sub-threshold morphine reward transmission in opiate dependent/withdrawn rats. Single unit recordings performed in neurons of the NAcc shell (but not core) confirm the modulatory role of BLA D1/D2 transmission in NAcc neuronal responses to morphine (1mg/kg;i.v.). Thus, blockade of intra-BLA D1 (but not D2) transmission blocks NAcc neuronal responding to morphine in opiate naïve rats, while blockade of BLA D2 (but not D1) receptors blocks neuronal responding to morphine in opiate dependent/withdrawn rats. Our results characterize and identify a novel and unique opiate addiction switching mechanism directly in the BLA, that can control the encoding of opiate reward information (behaviourally and neuronally) as a direct function of opiate exposure state, via D1 or D2 receptor signalling.

  • 16th November
    2010
  • 16

The Effects of Corticotropin-Releasing Factor on Dopamine Release: Implications for Reward and Effort

Take home messages: 

  • Corticotropin releasing factor (CRF) acts in the ventral tegmental area (VTA), a primary source of dopaminergic neurons and an integral part of the mesolimbic reward pathway, to regulate dopamine (DA) neurotransmission. 
  • A large reward (large reward magnitude)  will enhance motivated behavior. 
  • A large reward magnitude also enhances DA release in response to cues and rewards.
  • CRF, a hormone and neurotransmitter implicated in the stress response (HPA axis), in the VTA will attenuate motivated behavior in a dose-dependent manner and this effect is not due to motor suppression. 
  • CRF in the VTA attenuates phasic DA release (burst DA release as opposed to a more gradual release) specifically to rewards, not the cues related to the rewards. 
  • Satiety (being full) will reduce motivated behavior (in this case the reward was food pellets) as well as DA release to rewards (but not cues). 

Author Abstract (Phillips, et. al) : Phasic dopamine release during reward and effort manipulations: Effects of corticotropin release factor. 

The effort an individual is willing to exert to obtain a reward is dependent upon one’s motivational state as well as the value of the reward. Contemporary theories of dopamine function suggest that dopamine release, particularly in the striatum, is involved with enabling high-effort behaviors. Motivated behaviors can be influenced by stressful stimuli and stress-released neuropeptides such as corticotropin-releasing factor (CRF). The behavioral effects of stress on motivation could involve the midbrain dopamine system as (i) stress increases dopamine levels, (ii) CRF is released into the midbrain during stress, and (iii) CRF increases the firing rate and potentiates glutamate receptor current in dopamine neurons. Thus, we hypothesized that CRF in the VTA will elevate phasic dopamine release and increase the effort exerted to obtain a reward. However, before addressing this pharmacological question it was important to first determine how natural manipulations of motivational state and reward magnitude influence phasic dopamine release during high-effort behaviors.

We utilized fast-scan cyclic voltammetry to examine phasic striatal dopamine release to rewards and reward-predictive cues in rats performing an operant task under a progressive ratio (PR) reinforcement schedule for natural reinforcers. In separate sessions, we assessed behavior and dopamine release in rats under different motivational states (food-deprived or free-fed) or working for rewards of different magnitudes. The cumulative number of rewards earned scaled with the reward size in a given PR session. Interestingly, we found that motivational state and reward size robustly scaled reward-evoked dopamine release, while cue-evoked dopamine release was less sensitive to these manipulations. After establishing the effect of natural manipulations, we next examined how CRF injections into the midbrain affected behavior and dopamine release during PR sessions. Contrary to our hypothesis, CRF injected into the midbrain lowered the breakpoint in PR sessions. Furthermore, CRF injections attenuated reward-evoked dopamine release but did not affect cue-evoked dopamine release. Together, these results suggest that CRF modulates motivated behavior by affecting either dopamine neurons responsive to reward delivery and/or inputs to the midbrain representing the delivery of rewards.