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Zheng, Z., Reggente, N., Lutkenhoff, E., Owen, A., Monti, M.

Amy Zheng presented this poster at SfN in Washington, D.C (2014)

SfN 2014 Poster

Brief: In this study we used probabilist tractography on diffusion tensor imaging data to look at the whole brain’s anatomical connectivity index with the Left and Right Thalamus for patients with varying disorders of consciousness. Using a searchlight mapping procedure, we trained a Support Vector Regression on all but one patient  and attempted to predict a left out subject’s “Coma Recovery Scale” value (leave-one-patient-out cross-validation). That is, we looked at each region in the brain and asked the question “Does this region’s connectivity with the thalamus provide us with significant predictive power in regards to a DOC patient’s level of awareness?”. We were able to capture a significant portion of the variance (upwards of 56% of the variance), especially when drawing features for the SVR from regions such as the Middle Frontal Gyrus, Superior Frontal Gyrus, Precuneus, Parietal Operculum, Postcentral Gyrus, Inferior Temporal, Lateral Ocipital cortex, and Supracalcarine Cortex. Of particular intrigue is the contra-lateral importance of these connections. Thus, the ability for the Thalamus to anatomically connect with these regions significantly predicts levels of consciousness.

Highlighted Figure:

Screenshot 2014-11-20 20.50.53

SfN 2014 Abstract:

A reliable neural biomarker would serve as a valuable prognostic indicator for the assessment of awareness in patients with disorders of consciousness (DOC). Previous research has suggested that DOC may reflect disconnections in the thalamocortical networks. In this current study, we used probabilistic tractography to investigate the structural connectivity between the thalamus and the rest of the brain in 23 patients with varying levels of awareness as measured by the coma recovery scale-revised (CRS-R). The CRS-R spans six subscales aimed at assessing overt consciousness: auditory, visual, motor, oromotor, communication, and arousal. We obtained a total CRS-R score for each patient by summing across all six-subscale scores, where a maximum total score would be 23 points. We employed a searchlight mapping approach by centering a 5mm sphere at each voxel in the brain. The thalamic-connectivity-index values of voxels within each sphere were used as predictors in a support-vector-regression. The predictive power of our model was assessed by a leave-one-patient-out cross-validation whereby we iteratively trained a support-vector-regression model on 22 subjects and applied that model to the left-out subject. The resulting vector of predicted CRS-R scores correlated with the actual CRS-R scores most strongly when the searchlight was centered in Middle Frontal Gyrus and Precuneus. More specifically, connections with the left thalamus in these regions accounted for upwards of 44% of the variance in CRS-R scores. Furthermore, lateral occipital cortext and Right Supracalcarine Cortex accounted for up to 56% of the variance in CRS-R scores. These results provide neural bases for the level of conscious awareness displayed by DOC patients. More specifically, this investigation highlights the importance of thalamo-prefrontal and thalamo-temporal circuits in establishing a dependable anatomical metric for calculating patients’ CRS-R scores. Such findings support the “disconnection syndrome” hypothesis by illustrating that decreases in structural connectivity throughout the brain correlates with degradations in conscious awareness.


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nuclei of the thalamus. Anatomical and functional evidence for participation in processes of
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connectivity connectivity during anesthesia-induced transitions in consciousness.
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5. Lutkenhoff, E.S., McArthur, D.L., Hua, X., Thompson, P.M., Vespa, P.M., & Monti, M.M.
Thalamic atrophy in antero-medial and dorsal nuclei correlates with six-month outcome
after severe brain injury. NeuroImage: Clinical, 3, 396-404. (2013)

Kommers, C.,, Reggente, N., Raccah, O., Rissman, J.

Cody Kommers, my research assistant, presented this poster at SfN in Washington, D.C (2014)

SfN 2014 Poster

SfN 2014 Abstract:

Although the hippocampus is well known to contribute to the storage and retrieval of long-term memories, emerging data suggests that the hippocampus may also contribute to the online maintenance of task-relevant representations in some tests of working memory. To the degree that hippocampal mechanisms serve to facilitate performance on short delay memory tasks, individual differences in hippocampal microstructure could contribute to across-subject variance in working memory performance. To examine the relationship between hippocampal structure and function, we obtained the diffusion-weighted images (DWI) of a large cohort of subjects from the Human Connectome Project MRI dataset. We used the DWI to compute diffusion tensor images (DTI), which in turn were used to generate whole-brain mean-diffusivity (MD) maps. MD in deep gray matter has been construed as an indirect measurement of local microstructural deficits (Kim et al., 2013). Thereby, we aimed to assess the underlying integrity of each subject’s hippocampal gray matter and use examine whether these measures can account for variance in memory performance across subjects. Hippocampal regions of interest (ROIs) were identified using Freesurfer’s automated segmentation algorithm. Average MD within the left hippocampus was found to be significantly correlated with performance on a Working Memory List Sorting Task. This result is consistent with prior work showing that hippocampal MD serves a predictor for verbal and visuospatial memory (Carlesimo et al., 2010). Furthermore, MD along the Fornix (acquired from the Johns Hopkins White Matter Atlas) also significantly correlated with performance on the same task. This result illustrates that in addition to local integrity, the health of the hippocampus’s primary output tract is equally as important in explaining behavior that purportedly depends on hippocampal circuitry. This current study extends these previous findings and contributes to the debate surrounding the role of the hippocampus in working memory. We plan to conduct further analyses aimed at characterizing the potentially important role of fronto-hippocampal connectivity in working memory performance.

Highlighted Results:

Screenshot 2014-11-20 20.30.49


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2) Rissman, J., et al. (2008). Dynamic adjustments in prefrontal, hippocampal, and inferior temporal interactions with increasing visual working memory load. Cereb Cortex, 18(7), 1618–1629.
3) van Vugt, M. K., Schulze-Bonhage, A., Litt, B., Brandt, A., & Kahana, M. J. (2010). Hippocampal gamma oscillations increase with memory load. J Neurosci, 30(7), 2694–2699.
4) von Allmen, D.Y., et al. (2013). Neural activity in the hippocampus predicts individual visual short-term memory capacity. Hippocampus.
5) Winston, G.P., et al. (2013). Structural correlates of impaired working memory in hippocampal sclerosis. Epilepsia, 54(7), 1143–1153.
6) Yee, L.T.S., et al. (2014) Short-term retention of relational memory in amnesia revisited: accurate performance depends on hippocampal integrity. Frontiers in human neuroscience 8, 16.
7) Van Essen, D.C., et al. (2013). The WU-Minn Human Connectome Project: An overview. NeuroImage 80(2013):62-79.
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9) den Heijer, T., et al. (2012). Structural and diffusion MRI measures of the hippocampus and memory performance. NeuroImage, 63(4), 1782–1789.
10) Carlesimo, G.A., et al. (2010). Hippocampal mean diffusivity and memory in healthy elderly individuals: a cross-sectional study. Neurology, 74(3), 194–200.


Westphal, A.J., Monti, M.M., Reggente, N., Yazdanshenas, O., & Rissman, J.

Andrew Westphal presented this work at an SfN Nanosymposium in Washington D.C (2014)

SfN 2014 Abstract:

The act of retrieving a memory for a specific episode of one’s past requires the coordination of brain networks involved in controlling access to mnemonic contents and representing and monitoring the stored information. This has been shown to invoke a brain connectivity profile that diverges somewhat from the brain’s intrinsic resting state organization (Fornito et al., 2012). However, it is not yet clear to what degree this “retrieval mode” brain state differs from that observed during other complex cognitive tasks. In order to examine this further, we performed a graph theoretical analysis on fMRI functional connectivity data patterns measured while participants (N = 20) alternated between the performance of episodic source memory retrieval, analogical reasoning, and visuospatial perception tasks. In order to avoid systematic confounds, we ensured that the tasks were matched for response demands, reaction times, and bottom-up visual processing. Following preprocessing, we extracted fMRI time-courses from each 40 sec task block and concatenated these across runs to generate task-specific time-courses. We next reduced our whole brain data set to 264 functional areas, identified by resting state parcellation and meta-analysis (Power et al., 2011) and defined as spherical regions of interest (5mm radius). Pairwise correlations were then computed between all pairs of nodes for each cognitive task, and the weakest connections were thresholded out at a range of sparsity values. To capture a key global property of brain network dynamics, we analyzed how much each task-set expressed a graph theoretic measure known as modularity (Newman, 2006), which assesses the amount of connectivity within identified networks versus between networks. Our data revealed that the memory retrieval task showed significantly reduced modularity in comparison to the reasoning and perception tasks, an effect that replicated across sparsity thresholds. This suggests that the memory task-set is characterized by more widespread connectivity across the brain. Strikingly, reduced modularity in individual subjects was diagnostic of fewer memory errors and improved source monitoring. Taken together, our results suggest that memory retrieval may benefit from lower modularity, presumably because otherwise competitive brain networks supporting externally-directed and internally-directed attention must work together to link environmental stimuli with an introspective mnemonic search process.


In 1641 Rene Descartes sat, ball of wax in hand, pondering the flexibility of material states and how such impermanence spoke to an object’s essence. Hundreds of years later, cognitive neuroscientists are probing into the recesses of the human brain, assessing its task-dependent states, and forming hypotheses regarding the underpinnings of its malleability. Just like Descartes’ transforming wax, the human brain is in a state of constant flux. Observed endogenously, this metamorphic phenomenon of the brain is known as consciousness. In a seemingly relentless pursuit, philosophers and scientists alike have been enthralled by the ever so evasive conceptualizations of consciousness. However, despite valiant efforts, a truly satisfying, all-encompassing theory has yet to emerge. Scientists’ hardships in this arena are entirely understandable. For, how does one yield a true understanding of something that is inherently numinous and ephemeral? Certainly the sophists grew tired of mere mind mulling on such topics and socially evolved into scientists. Scientists, in succession, have turned to sophisticated technologies for insights into the critical cortical loci necessary for conscious awareness. However, is it possible to understand all the components of an object and be immediately privy to a comprehension of its emergent properties? The scientific community’s quest for an understanding of consciousness thus far is reminiscent of the story of the blind men trying to explain what an elephant is by each touching different parts. While recent advances in neuroimaging have allowed for researches to capture the spatio-temporal signature of brain activity during a plethora of mental states, brain mapping still remains unsatisfactory in its attempts to grasp consciousness.
Perhaps philosophy and science alone are incapable of providing the exploratory tools necessary for a succinct understanding of consciousness. In a non-mutually exclusive third branch of consciousness exploration reside the psychonauts; a nomenclature given to those who use a variety of methodologies to both achieve and describe altered states of consciousness. Conceivably, psychonautic experiences may be able to compliment the rigorous approaches currently employed by scientists and philosophers and yield a harmonious explanation for the universe’s greatest mystery. It will be the focus of this paper to elucidate plausible and safe methodologies for the merging of philosophy, science, and psychonautics while subsequently addressing the ethical dilemmas that arise from such a hypothetical collaboration. At first, this paper will speak to the neuroscientific correlations of brain structure with altered conscious states. Subsequently, this paper will address the potential for the recreation of those conscious states by the use of neuromodulatory devices. Lastly, it will lay forth the potential repercussions and ethical issues associated with such practices.

Since the advent of phrenology, it appears as though mankind’s desire to understand the functioning of the brain has taken manifest as a brain-mapping effort that that seeks to correlate localized regions of the brain with specific modules of function. Galen of Greece (210 BC) was the first to correlate structure and function with his focus on the pineal gland’s role in producing ““psychic pneuma”, a fine, airy substance which he described as “the first instrument of the soul”(Rocca, 2003). Since, ancient, medieval, and renaissance philosophers continued to suggest that the pineal gland provided the “seat for the soul”. Currently, a vast array of neuroscience methods, including direct recordings, neuroimaging, and behavioral testing after localized brain damage, have allowed researchers to relate various brain structures with various behaviors. For example, the hippocampus has long been associated with the acquisition of new memories (Squire, 1992), the prefrontal cortex in cognitive control (Miller and Cohen, 2001), and the superior parietal cortex with spatial attention (Yantis et al., 2002). However, the reported existence of complex brain networks, where multiple cortical regions are activated in unison for particular genres of task states, has gained significant traction as a theory for dynamic cognitive function (Bullmore and Sporns, 2009; Sporns et al., 2004). Such theories seems to suggest that the concurrent, temporally locked activation of a multitude of brain regions gives rise to the emergent phenomenon of consciousness, whereby different collections of brain regions result in different states of consciousness.
Research into the more ethereal states of consciousness has followed in similar suite to the rest of neuroscience’s ventures. That is, studies, while small in number, have pinpointed the different brain regions correlated with being in a state of meditation (Short et al., 2010; Lazar et al., 2000), trance (Peres et al., 2012), psychedelic states (Carhart-Harris et al., 2012), and sleep (Horovitz et al., 2008). These studies have paralleled the biochemical pursuits that attempt to identify the neurotransmitters whose presence in the brain is modulated by the ingestion of particular substances. For example, dopamine release has been affiliated with the use of cocaine (Ritz, 1987); serotonin with the use of lysergic acid diethylamide (LSD) (Nichols, 2004). Curiously, particularly potent psychedelic experiences, like those accomplished by drinking ayahuasca, rely on the ingestion of dimethyltriptamine (DMT), a compound found endogenously in mammalian species (Franzen and Gross, 1965). Furthermore, for the first time, DMT, and its precursors have been found in the pineal gland of rodents (Barker et al., 2013). This parallels the findings that dopamine is stored and released by specific brain areas, such as the pars compacta portion of the substnatia nigra (Geffen, 1976).
Attempts to establish double-dissociations for the supposed responsibilities of brain areas in particular cognitive functions has led researchers to implement neuromodulatory tools that can selectivity potentiate and deactivate particular brain regions. Subsequent alterations in behavior in relation to the external modulation of cortical regions allow researchers to make claims that follow the format of “if region X is potentiated, then subject’s perform Y% better at task T”. Techniques such as transcranial direct-current stimulation (tDCS) and repetitive transcranial magnetic stimulation (rTMS) have been used with great success to confirm the significance of a brain region’s involvement with particular behavioral tasks (for a review see Levasseur-Moreau et al., 2013).

However, in accordance with the brain-network theories illustrated previously, it would seem as though the simultaneous stimulation of multiple sites would be necessary to invoke a subjective change in conscious state. TMS has been shown to alter the functional connectedness of brain networks with the stimulation of single nodes within that network (Pascual-Leone et al., 2000). Yet, the network activation is not a perfect rendition of the endogenously induced conscious state. Furthermore, the limitations of both TMS and tDCS (e.g their lack of spatial specificity and inability to modulate cortical regions deeper than 1.5cm of cortex) prevent the faithful activation of particular networks. Perhaps this is the reason behind why rTMS has highly variable evidence on inducing changes in conscious states such as depression (Loo and Mitchell, 2005) and no studies have been published reporting shifts in consciousness that parallel those reported by psychonauts. Fortunately, recent technological developments such as low intensity focused ultrasound pulsation (LIFUP) allow for far more acute spatial resolution (2mm) compared to rTMS (5cm) and tDCS. Additionally, LIFUP has the potential to practically stimulate any region in the brain since it can focus on brain regions greater than 15cm past the skull (Bystritsky et al., 2011).

It can be theoretically postulated that if we can both identify networks of regions in the brain that are correlated with particular cognitive states and also precisely modulate brain activity, then we should be able to recreate particular conscious states exogenously. For example, if a subject were to ingest psilocybin and undergo an fMRI scan during the transition from normal waking consciousness to a psychedelic state, similar to Carhart-Harris et al. (2012), then a time-course of their brain activity would elucidate the transient activity of critical brain networks responsible for inducing the alteration in consciousness. Then, a precisely positioned array of LIFUPs aimed at the key nodes of interest could then reproduce the time-course of brain activity, remaining faithful to the spatial regions of interest and their fluctuations. Furthermore, LIFUP could be used to modulate the release of state-related neurotransmitters that have their locus in particular brain regions. If the adage that “the brain creates the mind” is coherent, then it should follow that this apparatus arrangement would recreate the psychedelic state that was initially experienced by the subject.
Of principal notation, this proposed use of mechanical means to induce psychedelic states has the incredible benefit of removing the chemical ingestion component of psychedelic experiences. Many psychonauts suffer the consequences of ignorance towards a particular substance’s exact contents, their source, and the dosage. Such gaps in knowledge lead to unwanted side effects and potential overdoses. Furthermore, the mere act of ingesting chemicals can cause incredible discomfort (e.g ayuhausca requires a purge; psilocybin results in stomach uneasiness; THC causes dry-mouth). The removal of the need to insert chemicals into the body is an insurmountable advantage of noninvasive stimulation that mirrors psychedelic states. Interestingly, it could be the case that some of the mental side effects of many psychedelics (e.g anxiety) have the potential be eliminated by tailoring the patterns of spatio-temporal LIFUP activations in a way that excludes brain regions responsible for such side effects. Additionally, the effects of such a stimulation procedure are potentially transient; it could be the case that the effects only persist during stimulation. As such, a psychedelic experience could last as long as the user desires. This comes in stark contrast to the unavoidable duration of substance-induced psychedelic experiences.

While such machine-induced mental states are hypothetically feasible, its actual implementation mandates both more reliable imagining methodologies and more robust neuromodulation devices. Nonetheless, the benefits, detriments, and ethics of such a concept are worthwhile topics of debate. The first points of discussion should be in regards to the concepts brought forth in the introduction of this paper: Does a mind in a psychedelic/altered state offer a more profound insight into the operations of natural phenomena (particularly that of consciousness)? Scientific documentations of behavioral reports following intravenous administration of DMT speak to subject’s revelations regarding consciousness:

Some subjects emerged from the intoxication with new perspectives on their personal and/ or professional lives. One said, “It changed m e. My self- concept seemed small, stupid and insignificant after what I saw and felt. It’s made me admit that I can take more responsibility; I can do more in areas I never thought I could. It’s so unnatural and bizarre you have to find your own source of strength to navigate in it.” Another “saw clearly how the personal self and consciousness are just slowed down and less refined versions of ‘pure consciousness.’ (Strassman et al., 1994)

Perhaps such shifts in perspective could help scientists to approach research questions from new angles. Imagine a coffee break that consists of a five-minute psychedelic journey for an “inspiration jolt” before tackling a seemingly unsolvable problem. Scientists routinely value the input of fresh perspectives, as seen by the incredible success of employing video game players to “solve puzzles for science” ( In an exemplary showcase, Francis Crick admitted to the effects of LSD in aiding his unraveling the structure of DNA, a discovery that won him the Nobel Prize (Rees, 2004). Hereby, it seems as though psychedelic states can issue thought-evoking and perspective-changing state of consciousness that may be of benefit to scientific discoveries.

Thus, it seems as though mechanically induced states of consciousness are theoretically conducive to creativity whilst void of the prolonged length of inebriation and potential pharmaceutical side effects. However, the potential benefits of psychedelics continue into their ability to aid psychotherapists achieve breakthroughs with their patients. For example, both LSD and psilocybin have been used to help terminally ill patients cope with the inevitability of their death (Richards, 1972; Grob et al., 2011). MDMA has been used to treat post-traumatic stress disorder with a 75% success rate (Bouso et al., 2008). Additionally, Psilocybin has been used to effectively increase “emotional insight” in psychotherapy (Carhart-Harris et al., 2012a). Eliminating the chemical side effects and tailoring the mechanical activations to not include brain-regions involved in the mental side effects of psychedelic states could increase the efficacy of these methods.

Unfortunately, substances initially developed for the sake of science and therapy has continually been met with illicit use. The frightening epidemic of oxycodone use is but one example of substance abuse that stems from pharmaceutical development. Therefore, the development of new technologies that could theoretically be used to alleviate pain, suppress consciousness, and other elicit other unforeseen effects should be treated with caution in order to avoid maladaptive practices. For example, at-home tDCS devices such as the ( have been reported to enhance the cognitive abilities of gamers. However, the long-term side effects of tDCS and its non-focal nature make it potentially dangerous and addictive. For, if a gamer sees improvements in their gameplay, then what is to stop them from increasing the voltage? Better yet, what incentive is there for them to ever stop using the device? This begs to ask the question: does the creation of publically available neuromodulation devices that can induce psychedelic states just create an easier way for people to become dependent on such systems?

Technically, the answer to the last question is “yes”. Just as the availability of a new substance creates an unlimited potential for its use, the introduction of a technology that could alter minds is equally likely to be recruited. However, humans have a seemingly insatiable and uncontrollable appetite for consciousness exploration as seen by the extensive history of trepanning and ayahuasca brews. Thereby it seems as though the development of such proposed neuromodulatory technologies is inevitable and its use most likely rampant. Thus, the legal ramifications that surround the use of such devices should be relatively lax, especially in light of the recent results of Portugal’s decision to decriminalize all drugs. Portugal’s drug use, crime rate, and national sickness decreased substantially after it’s nationwide decriminalization of drugs: “The data show that, judged by virtually every metric, the Portuguese decriminalization framework has been a resounding success” (Greenwald, 2009). Thereby, it seems as though the true problem with drug-use is legislation. Seeing as drug-use is concerned with perturbations of consciousness, it should follow then that the true problem with altered states of consciousness is legislation. Consequently, legislation should be put in place that exerts little to no regulations on the use of this hypothetical technology for consciousness exploration.

Furthermore, it should be considered unethical for legislatures to ban “states of consciousness”, since, with this technology, there would be no possibility for “possession” charges other than the possession of the device (which could easily be skirted around in the same way that “bongs” are sold for tobacco use only). Thus, preventing the use of this technology would be akin to a direct ban on states of consciousness, which seems highly unethical. For, are we not free to modulate ourselves as we see fit? It would appear that in the physical domain, there are no daunting restrictions. For example, body-builders routinely use weights to alter their physical appearance; chiropractors use electricity to increase muscle tone in their patients; plastic surgeons essentially rely on physical modifications. A society that regulates mental explorations that have absolutely no effect on the well being of the population at large should be considered dystopian. Unfortunately, current legislature in the majority of the world regulates the possession of illicit substances with penalties as severe as death. Regulations concerning the possession and use of substances that are conducive to violence (e.g bath salts) have a utilitarian benefit in their restrictions and are justified. However, such penalties seem outlandish for drugs that affect only the user. The proposed technologies should be governed under a legislation that finds a balance between allowing the safest possible administration of consciousness alterations while preventing the creation of states of consciousness that promote violence. Governments should even go so far as to encourage the use of technologies that act as safe alternatives to users that currently rely on physical chemicals. Such encouragement would be an inspiring extension on Portugal’s needle exchange program, which reduced the nation’s rate of infection, AIDS, and more.

In summation, it would appear as though there is feasibility for a technology that can mimic the conscious states experienced by those who use psychedelic substances. Such possibility is created by a small leap of theory that draws from recent advances in neuroimaging (e.g fMRI) and neuromodulation devices (e.g LIFUP). As a result, users can achieve the desired inspirational effects of psychedelics and simultaneously remove a majority of the potential for chemical induced harm. Such affects can aid scientific discoveries, decrease crime, and increase health. Lastly, the legislature of such technologies should be treated with relative leniency so as to optimize the utilitarian outcomes of this beneficial technology.


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Very proud of my research assistants(first and second authors) putting this one together!


Kommers, C.1,+, Raccah, O.1,+, Reggente, N.,1 Rissman, J1,2

Although the hippocampus is well known to contribute to the storage and retrieval of long-term memories, emerging data suggests that the hippocampus may also contribute to the online maintenance of task-relevant representations in some tests of working memory. To the degree that hippocampal mechanisms serve to facilitate performance on short delay memory tasks, individual differences in hippocampal microstructure could contribute to across-subject variance in working memory performance. To examine the relationship between hippocampal structure and function, we obtained the diffusion-weighted images (DWI) of a large cohort of subjects from the Human Connectome Project MRI dataset. We used the DWI to compute diffusion tensor images (DTI), which in turn were used to generate whole-brain mean-diffusivity (MD) maps. MD in deep gray matter has been construed as an indirect measurement of local microstructural deficits (Kim et al., 2013). Thereby, we aimed to assess the underlying integrity of each subject’s hippocampal gray matter and use examine whether these measures can account for variance in memory performance across subjects. Hippocampal regions of interest (ROIs) were identified using Freesurfer’s automated segmentation algorithm. Average MD within the left hippocampus was found to be significantly correlated with performance on a Working Memory List Sorting Task. This result is consistent with prior work showing that hippocampal MD serves a predictor for verbal and visuospatial memory (Carlesimo et al., 2010). This current study extends these previous findings and contributes to the debate surrounding the role of the hippocampus in working memory. We plan to conduct further analyses aimed at characterizing the potentially important role of fronto-hippocampal connectivity in working memory performance.

+ These authors contributed equally to this effort.

1 – Dept. of Psychology, University of California, Los Angeles

2 – Dept. of Psychiatry & Biobehavioral Sciences, University of California, Los Angeles




Kim, Hengjun J., et al. “Alterations of mean diffusivity in brain white matter and deep gray matter in Parkinson’s disease.” Neuroscience letters 550 (2013): 64-68.


Carlesimo, Giovanni A., et al. “Hippocampal mean diffusivity and memory in healthy elderly individuals: A cross-sectional study.” Neurology 74.3 (2010): 194-200.


Westphal, A.J., Reggente, N., Ito, K., Fortuna, W.H., Nawabi, Y., Milstein, M., & Rissman, J.


 SfN 2013 Abstract

Episodic memory and analogical reasoning tasks tend to engage many common frontoparietal structures, perhaps owing to their common demands for declarative memory retrieval and relational integration. Regions of the medial temporal lobe (MTL), well known to play a critical role in the encoding and retrieval of episodic memories, have also been shown to contribute to relational reasoning. We aimed to expand upon these findings by performing a direct comparison of memory- and reasoning-related MTL activity profiles and assessing how these regions communicate with distinct cortical networks to support different task demands. We examined fMRI activity and functional connectivity (FC) of the hippocampus (HIP), parahippocampal cortex (PHC), and perirhinal cortex (PRC) in a novel experimental paradigm featuring closely matched memory and reasoning tasks, both requiring judgments on 4-word stimulus arrays. One day prior to fMRI scanning, subjects (N = 20) encoded 80 words under two different mental imagery conditions. During the scanned memory task, subjects were to identify the word they previously studied and specify the encoding context, if possible. During the analogical reasoning task, subjects were to assess if the top and bottom word pairs shared the same semantic relationship or else indicate the number of non-analogous semantic relationships. Univariate parameter estimates extracted from HIP, PHC, and PRC all showed greater activity for source retrieval versus item familiarity. Activity in the PRC was significantly greater for correct versus incorrect source judgments; this effect also trended in HIP and PHC. During the reasoning task, HIP and PHC showed significantly greater activation on trials with valid analogies than on trials with no semantic relationships, whereas PRC activated strongly during all reasoning task conditions where semantic relationships were present. Task-dependent FC contrasting reasoning and memory was analyzed using psychophysiological interactions analysis. Left HIP demonstrated preferential coupling with both default mode and cognitive control network (CCN) structures for memory and bilateral MTL and lateral temporal regions for reasoning. Left PHC showed preferential coupling with CCN structures for memory and the supramarginal gyrus for reasoning. Left PRC demonstrated stronger coupling with precuneus for memory and occipital structures for reasoning. Taken together, these results confirm prior findings of MTL involvement in episodic source retrieval, while also documenting putative MTL contributions to analogical reasoning and distinct profiles of cortical network coupling across task sets.

Westphal, A.J., Reggente, N., Ito, K., Fortuna, W., & Rissman, J.


 HBM 2013 Abstract

Resting state fMRI connectivity analyses have identified a number of distinct functional brain networks, including the fronto-parietal task control network (FPTCN), the dorsal attention network (DAN), and the default mode network (DMN) (e.g., Vincent et al., 2008, Power et al., 2011). While these networks are typically defined based on intrinsically correlated BOLD fluctuations during periods of undirected thought, engagement of these networks is also observed during goal-oriented cognition. For instance, the FPTCN has been shown to co-activate with the DMN to facilitate internally-focused mentation and with the DAN to promote externally-focused attention (Spreng et al., 2010). In the present investigation, we sought to evaluate the degree to which task-set representations, particularly those requiring relational integration such as analogical reasoning and episodic memory retrieval, could be decoded from functional connectivity patterns within and between these networks. We were most interested in examining the representational content of connections originating in the rostral prefrontal cortex (RPFC), since RPFC may play a key role in relational integration, in addition to supporting the maintenance of superordinate goal-states (e.g., Badre & D’Esposito, 2009).

20 subjects healthy adult subjects underwent fMRI scanning (3T Siemens Trim Trio scanner, TR = 2 s, voxel size = 3 x 3 x 3.7 mm), performing alternating blocks of analogical reasoning, episodic source memory retrieval, and visuospatial attention tasks. These tasks were closely matched for reaction times, response demands, and bottom-up visual stimulus processing (all trials involved 4-word arrays, with the tasks only differing in what subjects had to decide about these words). Our data analysis procedure involved calculating the pairwise correlations between the concatenated BOLD time-courses for each task for each of 264 functional areas (10 mm spheres, identified by Power et al., 2011). We then supplied a regularized logistic regression classification algorithm with the full connectivity matrix from a given network (within-network connectivity) or from the set of connections that linked a pair of networks (between-network connectivity). All classification analyses used a leave-one-subject-out procedure, such that the classifier was trained on the connectivity data from 19 of 20 subjects and then applied to predict the task-sets associated with the remaining connectivity matrices from the held-out subject.

Using correlations between all 264 nodes, our classifier was 100% accurate at differentiating between the three cognitive task-sets. When trained solely on the correlations between the 16 RPFC nodes, the classifier was unable to differentiate between the reasoning and memory task-sets, indicating that within-RPFC connectivity patterns are not necessarily diagnostic of task-set. However, when trained on the correlations between RPFC nodes and nodes outside of RPFC, classification accuracy was quite robust (Fig. 1), reaching accuracy levels of up to 85% depending on which network was paired with RPFC. This result provides novel evidence that RPFC flexibly adjusts its interactivity with all three of the core networks to facilitate both internally and externally-oriented cognition.

By measuring the pattern of correlations between distinct nodes in a subject’s brain, one can reliably decode information about that subject’s cognitive task-set, even when a classifier has not been trained on data from that subject. The connection strengths between RPFC nodes and nodes in other core brain networks can be used to predict whether a subject is engaged in analogical reasoning or episodic source memory retrieval, despite the common demands of these tasks for relational integration. Given its position at the apex of a rostral-caudal hierarchy (Badre & D’Esposito, 2009), these data suggest that RPFC may differentially collaborate with posterior networks depending on task goals.



Vincent, J. L., Kahn, I., Snyder, A. Z., Raichle, M. E., & Buckner, R. L. (2008). Evidence for a frontoparietal control system revealed by intrinsic functional connectivity. Journal of neurophysiology100(6), 3328-3342.

Spreng, R. N., Stevens, W. D., Chamberlain, J. P., Gilmore, A. W., & Schacter, D. L. (2010). Default network activity, coupled with the frontoparietal control network, supports goal-directed cognition. Neuroimage53(1), 303-317.

Badre, D., & D’Esposito, M. (2009). Is the rostro-caudal axis of the frontal lobe hierarchical?. Nature Reviews Neuroscience10(9), 659-669.

Power, J. D., Cohen, A. L., Nelson, S. M., Wig, G. S., Barnes, K. A., Church, J. A., … & Petersen, S. E. (2011). Functional network organization of the human brain. Neuron72(4), 665-678.

Cho, S., Moody, T.D., Fernandino, L., Mumford, J.A., Poldrack, R.A., Cannon, T.D., Knowlton, B.J., & Holyoak, K.J. (2010). Common and Dissociable Prefrontal Loci Associated with Component Mechanisms of Analogical Reasoning. Cerebral Cortex, 20(3),524-533.

Westphal, A.J., Reggente, N., Nawabi, Y., & Rissman, J.


CNS 2013 Abstract


The rostral prefrontal cortex (RPFC), positioned at the apex of the prefrontal processing hierarchy, has been implicated in a diverse array of high-level cognitive processes including analogical reasoning and episodic memory retrieval—tasks that may share demands for relational integration. However, because reasoning and memory tasks have not been compared in the same studies, the degree of neuroanatomical overlap is unclear. To address this gap, we developed an fMRI paradigm that required subjects to periodically shift between Reasoning, Memory, and Perception tasks, closely matched for response demands, reaction times, and bottom-up stimulus processing. On all trials, participants were presented with an array of four words, with the cognitive operations to be performed on this array specified by a task set cue provided at the beginning of each block. Although RPFC regions showed highly overlapping recruitment during successfully solved analogy and source memory retrieval trials, without significant univariate differences, multi-voxel pattern analysis identified areas of RPFC wherein local activity patterns could facilitate robust decoding of these trial types. One such prominent cluster in left lateral RPFC was then seeded in a psychophysiological interaction analysis. Strikingly, this region showed divergent profiles of functional connectivity across task blocks, coupling more strongly with frontoparietal control network structures during Reasoning and with default mode network structures during Memory. These findings suggest that common areas of RPFC may differentially contribute to analogical reasoning and episodic retrieval via their coordinated interactions with distinct brain networks that respectively facilitate the integration of complex semantic or episodic relationships.



CNS 2014 Abstract: Nikolaidis, A., Reggente, N. et al


Using the the task-dependent functional connectivity across nodes within established cortical network from both before and after videogame training, we were able to asses the “plasticity” of these networks as a function of training. The plasticity of these networks, combined with graph theoretical metrics were used as features in a leave-one-out Ridge Regression that was able to account for upwards of 80% of the variance in individual difference scores in learning. Each network contributed varying levels of accuracy to classification depending on its involvement in the subject’s instructed priorities within the task. For example, plasticity in the Cingulo-Opercular network preferentially predicted(upwards of 55% of variance accounted for) learning in a training strategy that relied more heavily on executive control of attention and goal directed behavior.

Predicting individual differences in cognitive gains from videogame training using machine learning analyses of fMRI functional connectivity patterns

Aki Nikolaidis1, Nicco Reggente2, Drew Goatz3, Kathryn Hurley3, Andrew Westphal2, Arthur F. Kramer1; 1University of Illinois, Urbana Champaign, Beckman Institute, 2University of California, Los Angeles, Psychology Department, 3University of Illinois, Bioengineering Department

One of the important questions in cognitive training, and learning and memory more broadly, is how pre-existing individual differences in brain connectivity influence the effect of training. In this study, we use the fMRI functional connectivity of multiple networks, including the frontal-parietal and motor networks, to predict individual differences in learning over the course of 30 hours of cognitive training with the Space Fortress videogame. We used various metrics of functional connectivity and graph theory-derived parameters from 45 young adult participants as features to train adaptive multivariate regression models. Using a leave-one-participant-out cross-validation procedure, we find that we can predict a significant percentage of the variance in learning performance (defined as pre-post differences in Space Fortress score). By analyzing the performance of different regression models, we find that distinct brain networks contain different types of information regarding individual differences in learning rate. Furthermore, using both support vector regression and ridge regression we demonstrate how different feature and model parameters have important effects on model performance, and we consider how these parameters may have limited previous research using such techniques. We discuss implications of our results for cognitive training, as well as the continued use of machine learning and graph theoretical analyses in cognitive neuroscience.

CNS 2014 Poster: Zheng, Z., Reggente, N. et al. CNS 2014


For this poster we used Diffusion Tensor Imaging (DTI) techniques to compute thalamo-cortical probabilistic tractography maps. That is, for every voxel in the Thalamus, we determined every other voxel in the brain’s probabilist structural connectivity with that voxel. We did this for a total of 23 patients diagnosed with disorders of consciousness that fell into one of three possible clinical stratification (Vegetative State(VS), Minimally Conscious State+(MCS+), Minimally Conscious State-(MCS-)). We utilized a support vector machine to observe the patterns local anatomical connectivity of regions of cortex with the thalamus unique to subjects within each of the three groupings. We then used this classifier to “diagnose” unseen subjects in an extensive cross-validation. At times, particularly when using the patterns of activity local to the left prefrontal cortex, we were able to achieve 100% accuracy when distinguishing between VS and MCS+. We used a searchlight-mapping technique to determine which regions in the brain were most informative to classification. We are hoping that this technology could be found useful as a diagnostic aid that relies on the underlying pathology of patients with disorders of consciousness as opposed to the purely behavioral diagnoses currently utilized.

CNS 2014 Abstract:

Disentangling Disorders of Consciousness: Insights from DTI and MVPA

Zhong A. Zheng1, Nicco Reggente1, Evan S. Lutkenhoff1, Adrian Owen2, Martin M. Monti1; 1University of California, Los Angeles, 2University of Western Ontario

The stratification of individuals surviving severe brain injury in Minimally Conscious State (MCS) and Vegetative State (VS) patients is, currently, entirely based on behavioral criteria. This approach is problematic for at least two reasons: (i) behavioral assessments are known to be susceptible to sizeable misdiagnosis (~40%); (ii) this stratification of patients is entirely blind to the underlying pathology. To address both issues, we employed diffusion probabilistic tractography to assess projections from thalamic nuclei in 8 MCS plus (+) patients, who exhibit high-level behavioral responses, 8 MCS minus (-) patients, who only show low-level responses, and 8 VS patients. Evaluation of thalamo-cortical connectivity revealed more connections from the lateral-group nuclei to prefrontal, motor, and sensory regions in MCS+, as compared to VS. Additionally, tractography maps from thalamic nuclei were used as patterns in a logistic regression classification scheme. Using the ventral lateral nucleus’ whole-brain tractography maps as patterns, a leave-two-patients-out cross-validation correctly classified 6/8 VS patients and 7/8 MCS+ patients. This classification relied mostly on increased thalamo-frontal connections in MCS+ patients, as compared to VS. These results suggest that DTI combined with machine learning classification may facilitate the diagnostic distinction between VS and subcategories of MCS by uncovering the neural markers and pathological changes underlying disorders of consciousness.

This work was a collaboration with Zhong (Amy) Sheng Zheng.



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