Entries in fMRI (4)


How Does Our Brain Assign Value to Food?

Fig. 1: Schematic representation of how our brain incorporates perception of food items into willingness to pay [ref 3].How do we decide what and how much to eat and how much we are willing to pay for food? We may think about these questions sometimes, but apparently, our brains actually “compute” food values when we make decisions about what to eat. These value signals have been found to possess regional specificity and recent research demonstrates that sub-regions within the orbitofrontal cortex (OFC), play unique roles [1]. The OFC is involved in higher-order cognitive functions such as decision-making and human brain imaging studies have begun to illustrate functional contributions of the OFC in food value computation. For example, several studies have indicated that the medial OFC encodes generalized value signals, independent of direct experience or consideration of future rewards, while the lateral OFC encodes specific value [2].

Recent work has elucidated the “constituent attributes” that underlie the construction of food value and how they are both represented and integrated in the OFC [1]. By using a food-based decision task in human participants, researchers found that a subjective sense of nutrients are important in assigning value to food; nutritive aspects of our food, such as protein, fat, carbohydrates and vitamins, appear to be important predictors of the subjective value of food. Multi-voxel pattern analyses (MVPA) of functional magnetic resonance imaging (fMRI) data revealed that both the medial and lateral OFC represent food value signals with the lateral OFC encoding for the basic nutritional aspects of food. The results of effective connectivity analyses between OFC sub-regions indicated that information in relation to subjective nutrient factors from the lateral OFC are then integrated at the time of valuation within the medial OFC, which “computes” overall values. More simply, the lateral OFC estimates the amount of nutrients and the medial OFC works out a weighted sum value, influencing behavior.

Understanding how a subjective value signal is generated in the lateral OFC and how inter-regional signals relate to more involved network representations remains elusive, yet these studies provide new data for further study with important implications for understanding neural and psychological mechanisms underlying food-valuation processes, salient for diseases in which these processes are out of balance, such as in eating disorders [1]. Further, these studies represent a conceptual advance which may eventually be generalized to other value judgments [3].




1. Suzuki, S.; Cross, L.; O’Doherty, J. P., Elucidating the underlying components of food valuation in the human orbitofrontal cortex. Nat. Neurosci. 2017, 20 (12), 1780-1786.

2. (a) Barron, H. C.; Dolan, R. J.; Behrens, T. E. J., Online evaluation of novel choices by simultaneous representation of multiple memories. Nat. Neurosci. 2013, 16 (10), 1492-1498 ; (b) Howard, J. D.; Gottfried, J. A.; Tobler, P. N.; Kahnt, T., Identity-specific coding of future rewards in the human orbitofrontal cortex. Proceedings of the National Academy of Sciences of the United States of America 2015, 112 (16), 5195-5200.

3. Pessiglione, M.; Wiehler, A., Breaking down a meal. Nat. Neurosci. 2017, 20 (12), 1659-1660.


Neural activity may differ between males and females with Adolescent Major Depressive Disorder

In a recent study, evidence of a sex difference in neural activation during a cognitive task was demonstrated in relation to adolescent major depressive disorder (MDD), with a novel focus on males [1]. There are differences between men and women in symptom presentation in MDD, and men are more likely to experience persistent, and women, recurrent, forms of depression [2]. By the age of 15, girls are two times as likely to experience depression compared to their male counterparts [3], whereas in adulthood, men are more likely to become suicidal [4].     

A recent study published in Frontiers in Psychiatry investigated depression in male and female adolescents between the ages of 11 and 17 [1]. Cognitive control of emotion, which also appears to differ between males and females, was tested using functional magnetic resonance imaging (fMRI) during an affective Go/No-Go task [1]. The participants’ responses to happy, sad or neutral words were measured during image acquisition. Neural activity in response to the sad words differed in the supramarginal gyrus in adolescent males compared to females [1]. Interestingly, depressed adolescent males showed decreased cerebellar activation and an age related decrease in its connectivity with the superior frontal gyrus compared to healthy adolescent males [1].

A number of brain regions found to be affected in adolescent males are involved in the default mode network, which is of interest as this network may be involved in the decline in cognition that occurs in MDD [5]. In light of sex differences related to MDD, the results of this study suggest that preventative and therapeutic interventions may be improved if neural differences are taken into consideration. It remains unknown whether developmental neural changes are involved in the etiology of this illness. As an important caveat, the study did encounter issues with enrollment, as fewer males participated compared to females, highlighting the need for matched sample sizes in future studies.



[1] Chuang J-Y, Hagan CC, Murray GK, Graham JME, Ooi C, Tait R, Holt RJ, Elliott R, van Nieuwenhuizen AO, Bullmore ET, Lennox BR, Sahakian BJ, Goodyer IM and Suckling J (2017) Adolescent Major Depressive Disorder: Neuroimaging Evidence of Sex Difference during an Affective Go/No-Go Task. Front. Psychiatry 8:119. doi: 10.3389/fpsyt.2017.00119


[2] Dunn V, Goodyer IM. Longitudinal investigation into childhood- and adolescence-onset depression: psychiatric outcome in early adulthood. Br J Psychiatry (2006) 188:216–22.


[3] Cyranowski JM, Frank E, Young E, Shear MK. Adolescent onset of the gender difference in lifetime rates of major depression: a theoretical model. Arch Gen Psychiatry (2000) 57(1):21–7.


[4] Blair-West GW, Cantor CH, Mellsop GW, Eveson-Annan ML. Lifetime suicide risk in major depression: sex and age determinants.  J Affect Disord. 1999 Oct: 55 (2-3): 171-8.  


The next five minutes could really help: Resting state fMRI predicts antipsychotic treatment response 

In Friday’s online issue of The American Journal of Psychiatry, Dr. Deepak Sarpal and colleagues published a ground-breaking new report where antipsychotic treatment response could be predicted using resting state fMRI.

Resting state function magnetic resonance imaging, or rs-fMRI for short, is a technique where changes in blood flow can be measured in the brain and plotted on the basis that increased blood flow means increased brain activity (and less blood flow means lower brain activity).  This method can reveal single hotspots (or coldspots) of activity, but with very high time resolution, can be used to identify how different regions of the brain are connected.  Using an identified hotspot as a ‘seed,’ fMRI analysis allows a mapping of when and where other changes happen in the brain during the resting period to create a network of functional connectivity.

Beginning with a ‘discovery’ cohort, Sarpal and colleagues found that in first-episode schizophrenia patients, analysis of a 5-minute rs-fMRI scan revealed that those who would later showed a lasting response to antipsychotic drug treatment (risperidone or aripiprazole) had lower connectivity stemming from the striatum.  The striatum is a region in the middle of the brain and, as a central part of the brain’s reward system, is known to have dysregulated function in schizophrenia. The current study found the striatum to be integrating measureable signals with 91 other functional connections.

By setting a threshold level of striatal connectivity, the authors found significant predictive power of their system in testing rs-fMRI data from a matched but independent ‘generalizability’ cohort of patients who were treated for an acute psychotic episode. Again, those patients who would go on to respond from antipsychotic therapy had subthreshold levels of striatal connectivity prior to intervention. 

A major step forward from this paper is identifying patients where treatment is likely to work – and at the same time, highlighting those patients who are likely to be treatment non-responders.

A key aspect of the work in our lab is in understanding the molecular changes associated with the normal and diseased brain. Using dual-modality imaging, we design experiments that can link fMRI with PET imaging to visualize specific molecules and enable understanding of how the regional density of a receptor/protein target relates to functional changes in blood flow. The recent findings by Dr. Sarpal et al could quickly open new doors to highlight what divides patient groups; by applying novel PET tools, we are poised to advance understanding of underlying protein targets could be exploited in next-generation therapeutics.


Sarpal DK, et al “Baseline Striatal Functional Connectivity as a Predictor of Response to Antipsychotic Drug Treatment” American Journal of Psychiatry, Aug. 28, 2015.

AJP in Advance (doi: 10.1176/appi.ajp.2015.14121571).


Can Dancing Improve your Ability to Remember?


A few weeks ago I was on the Green line heading to North Station when I realized that a young woman a few seats away was carrying a pair of tap shoes. My dance background is quite strong, but I haven’t put on my tap shoes in three years. I first started dancing at age three when my mom, some-what frustrated with my high-energy antics, signed me up as a way to tire me out. When I was packing for my summer in Boston, I brought my tap shoes because I knew I wanted to get back into it.

Long story short, I stopped this woman after we got off the train. She recommended a studio for me to look up, and I have been going to tap class once a week ever since.

What surprised me the most about getting back into my shoes was my ability recall dances that I have not seen or performed in years. My dance memory is far better and more accurate than most of my memory. I can even recall dances that I learned for the first time over a decade ago.

Upon investigating the connection between dancers and good long-term memory, I wanted to know what happened in the brain in response to high-intensity dance training and if there were changes in way new long term memories are created or stored. I found that studies have shown that dancers are able to use mental imagery better and with higher reproducibility than non-dancers even in laboratory settings (Blasing et al., 2012). Many areas of the brain are activated during motor learning, included many overlapping areas which could improve devoted concentration and therefore is thought to create a stronger memory. In a case-study, dancers were able to recall dances learned from over three years previously (Steven et al., 2010). The brain function behind long-term kinestetic sequence memory (dance is considered a sequence of steps) is currently not known and is difficult to study. Most studies have focused on ways to disrupt this long-term memory and have not been designed to determine how the disruptions are occurring in the brain, perhaps due to limited tools to study the brains of humans till relatively recently.

Scientists have used both fMRI and PET to study the brains of dancers, but it doesn’t appear that there is much current study using these techniques on long-term dancer memory. Typically, subjects have to remain as still as possible in the large scanners required for these studies. However, a group recently found a way to let ballroom dancers move through the steps with their feet on an inclined apparatus while lying in a PET scan (Blasing et al., 2012). They were able to see activated regions of the brain which were exclusively associated with dancing. This could open the door to more kinesthetic memory based studies using PET and fMRI.


For more information on what we do know about the brain and dance see: Nerurocognitive Control in Dance Perception and Performance (Blasing et al., 2012)

For more information on dance and long-term memory see: Backwards and Forwards in Space and Time: Recalling Dance Movement from Long-Term Memory (Steven et al., 2010)