Human visual cortex area V2 is necessary for visual awareness

The human visual cortex (that encompasses posterior parts of the occipital lobes in the very back of the brain) is composed of multiple functionally distinct areas. According to classical hierarchical processing models, neurons in the primary visual cortex (also known as V1) are sensitive to fairly simple visual stimulus features (such as lines of certain orientation), and as one progresses from the V1 to the neighboring area V2 (and from V2 to higher order areas) inputs converge so that neurons begin to respond to increasingly complex visual features, such as perceptual objects (e.g., chairs, cows, hats) in the lateral occipital complex. What has puzzled researchers, however, is the point(s) at which visual awareness takes place in this processing chain; while there are studies indicating that removal of/damage to V1 results in lack of visual awareness, it is possible that this is due to V1 distributing information to higher-order areas, rather than V1 generating visual awareness per se.

Salminen-Vaparanta and colleagues, by inducing currents on the cortical surface using transcranial magnetic stimulation (TMS), specifically disturbed the functioning of area V2 in healthy volunteers (N.B. the disturbance of a cortical area using TMS is highly transient and does not produce any longer-lasting adverse effects). During this transient disruption of area V2, the subjects lost awareness of visual stimuli that were presented to them. Specifically, suppressing the V2 (without concomitant suppression of V1) 44-84 ms from the onset of a visual stimulus resulted in lack of conscious percept of the stimulus. The results of Salminen-Vaparanta thus suggest that area V2 is necessary for conscious visual experience. Methodologically, their study nicely demonstrates how TMS can be utilized to probe the role of various cortical areas in higher-order cognitive functions, such as visual awareness.

Reference: Salminen-Vaparanta N, Koivisto M, Noreika V, Vanni S, Revonsuo A. Neuronavigated transcranial magnetic stimulation suggests that area V2 is necessary for visual awareness. Neuropsychologia (2012). http://dx.doi.org/10.1016/j.neuropsychologia.2012.03.015

Inflammatory state augments orbitofrontal cortex responses to negative pictures

While there have been several interesting studies reporting associations between inflammatory state and clinical depression (see, for instance, Irwin & Miller 2007), the potential underlying neural mechanisms have remained largely unexplored. In a recent study by Jennifer Kullmann et al. published in Human Brain Mapping (currently available online as a pre-publication "early view" article), healthy volunteers were given an injection of either saline or bacterial lipopolysaccharide (0.4 ng/kg) that caused an acute inflammatory reaction, including rise in body temperature, and increase in plasma levels of pro- and anti-inflammatory cytokines and cortisol. The effects of acute inflammation on brain responses to negative-valence aversive pictures vs. emotionally neutral pictures was then investigated using functional magnetic resonance imaging.

The authors observed that the activation to presentation of negative-valence pictures of especially right-hemisphere inferior orbitofrontal cortex (at lower statistical threshold also several other brain structures) was augmented during acute inflammatory response. Given that the orbitofrontal cortex has been in previous studies associated with emotion-regulation (e.g., inhibition of amygdala activity during suppression of emotional responses) and production of affective states in response to emotional stimuli, the authors interpreted their findings as indicating that the subjects were more susceptible to the emotion-inducing effects of the aversive pictorial stimuli during the peripheral inflammatory response. These findings are highly interesting as they disclose a potential mechanism through which inflammatory state modulates affective processing and may thus play a role in the development of mood disorders.

Curiously, a recent Cochrane meta analysis indicated that mirtazapine, an older antidepressant that has antihistaminergic effects (that reduce inflammatory response) in addition to it's effects on various 5-HT receptors, was more effective in the treatment of clinical depression than the newer selective serotonin re-uptake inhibitors (Watanabe N et al. 2011). There are also findings suggesting that co-administration of an anti-inflammatory drug with selective serotonin re-uptake inhibitors improves treatment outcome in patients suffering from clinical depression (Akhondzadeh S et al. 2009). Overall, these findings highlight the important principle that the brain, and thus disorders of brain function, is never quite separate from the rest of the body (or the environment), but rather that brain function is significantly intertwined with bodily functions.

References:

Akhondzadeh S, Jafari S, Raisi F, Nasehi AA, Ghoreishi A, Salehi B, Mohebbi-Rasa S, Raznahan M, Kamalipour A. Clinical trial of adjunctive celecoxib treatment in patients with major depression: a double blind and placebo controlled trial. Depression and Anxiety (2009) 26: 607-611. http://dx.doi.org/10.1002/da.20589

Irwin MR, Miller AH. Depressive disorders and immunity: 20 years of progress and discovery. Brain, Behavior, and Immunity (2007) 21: 374-383. http://dx.doi.org/10.1016/j.bbi.2007.01.010

Kullmann JS, Grigoleit JS, Lichte P, Kobbe P, Rosenberger C, Banner C, Wolf OT, Engler H, Oberbeck R, Elsenbruch S, Bingel U, Forsting M, Gizewski ER, Schedlowski M. Neural response to emotional stimuli during experimental human endotoxemia. Human Brain Mapping (2012). http://dx.doi.org/10.1002/hbm.22063

Watanabe N, Omori IM, Nakagawa A, Cipriani A, Barbui C, Churchill R, Furukawa TA. Mirtazapine versus other antidepressive agents for depression. Cochrane Database of Systematic Reviews (2011) 12. Art. No.: CD006528. http://dx.doi.org/10.1002/14651858.CD006528.pub2

Diffusion imaging reveals anatomical connectivity and microstructural changes due to learning

Diffusion imaging is a method where magnetic resonance imaging is utilized to measure movement of water within the brain; in modern diffusion imaging sequences water movement is measured in several tens of directions. Since the glia cells and neurons that make up the brain tissue obstruct free diffusion of water, there are significant deviations from Brownian (i.e., random) motion in most brain structures (other than ventricles of course). What makes this phenomenon really interesting is that by measuring the directions of local diffusion, it is possible to reconstruct the white matter tracts of the brain (as water flows along the direction of the myelinated neural fibers) and thus inspect anatomical connectivity of the brain. A recent paper by Dr. Wedeen and colleagues published in Science shows how accurately the anatomical connectivity of human brain can be measured non-invasively in healthy volunteers. This paper nicely combines the vast improvements that have recently taken place in both diffusion imaging sequences as well as data analysis methods.

As another highly interesting recent publication on diffusion imaging, it was shown by Sagi et al. in Neuron that there are rapid changes in diffusion properties of focal brain structures that correlate with learning. In this study, diffusion was measured prior to and immediately after volunteers were intensely playing a car-racing game where they had to learn to navigate the racetrack. One control group was playing the same game but with changing racetracks so that their spatial learning was not to the same extent engaged during the gameplay. Compared to pre-game diffusion measures, there were microstructural changes revealed by diffusion imaging after two hours of racing in several brain structures and, furthermore, learning the racetrack correlated with microstructural changes in the right-hemisphere parahippocampus. These results are really fascinating as they suggest that structural imaging can be utilized to measure short-term plastic changes in the human brain.

References:

Sagi Y, Tavor I, Hofstetter S, Tzur-Moryosef S, Blumenfeld-Katzir T, Assaf Y. Learning in the fast lane: new insights into neuroplasticity. Neuron (2012) 73: 1195-1203. http://dx.doi.org/10.1016/j.neuron.2012.01.025

Wedeen VJ, Rosene DL, Wang R, Dai G, Mortazavi F, Hagmann P, Kaas JH, Tseng WY. The geometric structure of the brain fiber pathways. Science (2012) 335: 1628-1634. http://dx.doi.org/10.1126/science.1215280

Cortical network properties predict language learning ability

Findings by Sheppard et al. published in the Journal of Cognitive Neuroscience, reveal interesting brain functional network properties that make it easier for some to learn words of a new language. The authors of this study used functional magnetic resonance imaging to map brain hemodynamic responses of a group of volunteers during a pitch discrimination task. Subsequently, the volunteers participated in another experiment where they were to learn words of an artificial (spoken) language. Interestingly, results of network analysis of brain hemodynamic data obtained during the pitch discrimination task predicted individual differences in spoken language learning ability.

Brain networks were analyzed by the authors by reconstructing the cortical surface of each subject and by dividing the cortex into ~1000 nodes. Person’s correlation coefficients were then calculated between hemodynamic response time series of each of the nodes and correlations exceeding a certain threshold value were considered as a functional connection between two nodes. Network analysis across all the nodes revealed differences between successful and less successful learners. Successful learners had higher global efficiency, meaning that there were, on the average, fewer edges separating the nodes of their cortical networks from each other. On the other hand, local efficiency measure was higher in the less successful learners, suggesting that their local network connectivity was higher than in successful learners. When analyzed across specific anatomical regions, it was further observed that these network differences could be observed in prefrontal and parietal cortical areas bilaterally as well as in the right temporal cortex.

Network analysis offers a powerful alternative method that complements the more traditional functional neuroimaging data analysis methods. With a network analysis it can be effectively measured how cortical areas work together to give rise to perceptual and cognitive functions. In this particular study, it was very nicely observed that network properties of brain function predicted language learning capability, and I anticipate that we will see in the near future a wealth of highly interesting findings in cognitive neuroscience that are based on network analysis methodology. Furthermore, it would be interesting to see whether cortical functional network properties differ between healthy individuals and those suffering from language disorders such as dyslexia.

Reference: Sheppard JP, Wang JP, Wong PC. Large-scale cortical network properties predict future sound-to-word learning success. Journal of Cognitive Neuroscience (2012) 24: 1087-1103. http://dx.doi.org/10.1162/jocn_a_00210

Movies as stimuli in cognitive neuroscience

In 2004, Dr. Uri Hasson and his colleagues published rather amazing findings in Science; they showed that brain hemodynamic activity patterns, measured with non-invasive functional magnetic resonance imaging, were highly replicable across individual volunteers who were freely viewing a 30 min clip from the feature film "The Good, the Bad and the Ugly" (dir. Sergio Leone, 1966). These findings elicited hopes for being able to use feature films in studies of perceptual and cognitive functions and, indeed, it was soon demonstrated that "higher-order" prefrontal cortical areas are also synchronized across subjects when viewing a feature film during brain scanning (Jaaskelainen et al. 2008). 

This week there was another step forward that is making it possible to use feature films in non-invasive cognitive neuroimaging studies. Lahnakoski et al. (2012) showed in their study published in PLoS ONE how annotating stimulus features that occur in a movie can be utilized in the analysis of the highly complex and spatiotemporally overlapping brain responses that are elicited when subjects are watching a movie. The stimulus feature time series were both used in a general linear model and correlated with independent components. The authors report that, taken together, the results encourage use of movie stimuli in non-invasive cognitive neuroimaging studies.

While the advances presented by Lahnakoski et al. are mostly methodological ones, feature films present exciting possibilities to any cognitive neuroscientist; they can be highly involving, capable of eliciting genuine emotions in experimental subjects, and often depict social interactions in a highly realistic manner along with all those subtle social cues that take place in real life. This way, movies can be highly effective in stimulating brain processes that underlie emotions and social cognition, thus potentially helping bridge one of the bigger gaps that still today exist between psychology and neuroscience.

References:

Hasson U, Nir Y, Furhmann G, Malach R. Intersubject synchronization of cortical activity during natural vision. Science (2004) 303: 1634-1640. http://dx.doi.org/10.1126/science.1089506

Jääskeläinen IP, Koskentalo K, Balk MH, Autti T, Kauramäki J, Pomren C, Sams M. Inter-subject synchronization of prefrontal cortex hemodynamic activity during natural viewing. Open Neuroimaging Journal (2008) 2: 14-19. http://dx.doi.org/10.2174/1874440000802010014

Lahnakoski JM, Salmi J, Jääskeläinen IP, Lampinen J, Glerean E, Tikka P, Sams M. Stimulus-related independent component and voxel-wise analysis of human brain activity during free viewing of a feature film. PLoS ONE (2012) 7: e35215. http://dx.doi.org/10.1371/journal.pone.0035215