Electroconvulsive Therapy Impairs Memory Reconsolidation

** This post is meant to be read in tandem with its more critical cousin, How Can We Forget? at The Neurocritic. **

Thymatron® System IV (Somatics, LLC)

“Memories are constantly changing, each time we recall them they're physically different.”
- me, July 7, 2006

The precision of memory over time is a quaint idea. A large body of research shows us that memories are not fixed entities (Alberini & Ledoux, 2013). Every time a specific memory “trace” is reactivated, it enters a transiently unstable state where it's subject to change before becoming consolidated and stored again (Nader & Hardt et al., 2009). In the most widely studied model systems, new protein synthesis in the hippocampus and/or amygdala is required for reconsoldation of fear memories.

Fig. 1 (Alberini & Ledoux, 2013). Two Views of Memory. In the reconsolidation view (bottom), when a memory is activated, the version stored during the last retrieval (rather than the version stored after the original experience) is called up.


Although these concepts and mechanisms of memory reconsolidation are not universally accepted, they've formed the basis for a thriving area of basic neuroscience research. Furthermore, the principles learned from animal studies have been applied to Pavlovian fear conditioning in humans (Schiller et al., 2010).

By precisely timing the presentation of a fear memory reminder (i.e., within the reconsolidation window), extinction of the skin conductance response to a conditioned stimulus (a colored square previously associated with a mild shock) occurred when tested 24 hours later (Schiller et al., 2010). A subset of participants returned one year later, and the “extinction-during-reconsolidation” procedure prevented reinstatement of the fear response, unlike in the group where extinction training was conducted outside the reconsolidation window.

This finding was greeted with optimism for potential future applications in treating anxiety disorders, including PTSD. However, sweaty palms in anticipation of a mild shock is not exactly the same as the trauma of a disfiguring accident or a sexual assault.

Now, a group of Dutch researchers (Kroes et al., 2013) has taken a completely different approach to disrupt reconsolidaton in humans – namely, by reactivating recently learned memories in depressed patients immediately before administration of clinically prescribed electroconvulsive therapy (ECT).

ECT is sometimes used as a last resort in treating chronically depressed patients who've failed to respond to pharmaceutical and psychological therapies. Despite its floridly negative depiction in Hollywood movies, ECT is generally accepted within the psychiatric community as a highly effective treatment for intractable major depression (Kellner et al., 2012).¹

The participants were 39 patients (mean age = 57 yrs) diagnosed primarily with moderate to severe recurrent major depressive disorder. They were either at the end of an acute treatment cycle or receiving maintenance ECT. The study used a between-subjects design with 3 different experimental conditions, with patients randomly assigned to Group A, B, or C (n=13 in each). The within-subjects factor was whether or not the patients received a reminder of previously learned material before treatment.

All participants learned two different emotionally charged slide stories with audio narration, each consisting of 11 images. In one, a boy is in an accident that severs his feet, which are reattached at the hospital. In the other, two sisters leave their home at night, and one is kidnapped at knife point and attacked by an escaped convict.

Memory for one of the stories was reactivated a week later by presenting part of the first slide, and then giving a test for this slide. The most surprising part comes next: only 4 minutes later (on average), Groups A and B were anesthetized and received ECT, which induced a seizure. Group C received their ECT treatment at a later date. The final memory test for Groups A and C was 24 hrs after the reminder, while Group B was tested as soon as they woke up from the procedure (mean = 104 min later). The final test consisted of 40 multiple choice questions about each of the stories.

Supplementary Fig. 1 (modified from Kroes et al. 2013). Study design. During the first study session, all groups were shown two emotional slide-show stories. During the second session, memory for one of the two stories was reactivated. Immediately after memory reactivation, patients in Groups A and B received ECT. For Group B, memory was tested immediately upon recovery from ECT (blue box). For Groups A and C, memory was tested one day after reactivation (red and orange respectively).


The basic idea here is that reconsolidation of the reactivated story isn't complete at 30 or 90 minutes, so Group B's test performance should be the same for the two stories. In contrast, reconsolidation is complete by 24 hrs, so for Group A the disruptive effect of ECT should selectively impair memory for the transiently reactivated story, which is in a labile state (relative to the "consolidated" story learned 7 days earlier).

And in fact, this is what the authors observed, as shown in the figure below. The horizontal dotted line depicts chance performance (25% accuracy) – no better than guessing. Group A performed at chance for the reactivated story, but remembered at least some of the non-reactivated story. In contrast, Group B performed significantly better than chance for both stories. Finally, Group C (the control group) remembered significantly more details about the reactivated story (relative to the non-reactivated story and compared to the other groups), since this served as a rehearsal opportunity that wasn't disrupted by ECT.

Fig. 1 (modified from Kroes et al. 2013). ECT disrupts reconsolidation. Memory scores on the multiple choice test are expressed as percentage correct (y axis). Memory for the reactivated story shown in solid bars and non-reactivated story in open bars. Each circle is the score for an individual patient. The horizontal dotted line is chance performance. Group A is in red, Group B in blue, and Group C in orange.


Although the number of patients in each group (and therefore the statistical power) weren't overwhelming, the study provides tentative evidence for the effectiveness of ECT in disrupting memories of the reconsolidated story. The potential import of this finding for future treatments is that the mere act of recalling highly unpleasant autobiographical memories immediately prior to ECT could assist in dampening future recall of these specific memories.

How practical is this idea? Would the ECT-induced amnesia be highly specific for the horrid memories, leaving pleasant ones intact? Read my companion post at The Neurocritic to find out.


Footnote

¹ An extensive review of the pros (e.g., effectiveness) and cons (e.g., memory loss) of ECT is beyond the scope of this post.


References

Alberini CM, Ledoux JE (2013). Memory reconsolidation. Curr Biol. 23:R746-50.

Kellner CH, Greenberg RM, Murrough JW, Bryson EO, Briggs MC, Pasculli RM. (2012). ECT in treatment-resistant depression. Am J Psychiatry 169:1238-44.

Kroes MC, Tendolkar I, van Wingen GA, van Waarde JA, Strange BA, & Fernández G (2013). An electroconvulsive therapy procedure impairs reconsolidation of episodic memories in humans. Nature neuroscience PMID: 24362759

Nader K, Hardt O. (2009). A single standard for memory: the case for reconsolidation. Nat Rev Neurosci. 10:224-34.

Schiller D, Monfils MH, Raio CM, Johnson DC, Ledoux JE, & Phelps EA (2010). Preventing the return of fear in humans using reconsolidation update mechanisms. Nature, 463 (7277), 49-53 PMID: 20010606

A Neural Circuit for Voracious Overeating in Mice: Translation to Humans

Optogenetic activation of inhibitory GABA neurons projecting from the limbic forebrain to the lateral hypothalamus causes this mouse to binge on cheese. The rapid onset and offset of the intense feeding behavior is striking. Credit: Jennings et al. (2013).


The hypothalamus is a collection of discrete nuclei in the vertebrate diencephalon that control a variety of metabolic, neuroendocrine, and circadian functions. Since the 1940s, the ventromedial nucleus (VM) has been known for its important role in satiety — lesions of this nucleus cause rats to become obese, while electrical stimulation of this structure curtails feeding. On the other hand, the lateral hypothalamus (LH) controls hunger. In 1953, Delgado and Anand implanted multilead electrodes into the brains of cats and found that electrical stimulation of the LH caused an increase of food intake to 500-1,000% of control levels.

Sixty years later, Jennings and colleagues (2013) set out to delineate the precise circuitry and neuronal population responsible for these effects using modern optogenetic techniques. They targeted a projection pathway from the bed nucleus of the stria terminalis (BNST), a part of the "extended amygdala" in the limbic forebrain, to the LH. These inhibitory GABAergic neurons synapse onto excitatory glutamatergic neurons in the LH.

This specific cell type was targeted by using a genetically modified mouse line. The mice express a recombination enzyme only in neurons that express the vesicular GABA transporter (vGAT-ires-cre mouse).  A viral construct was used to insert a gene that codes for Channelrhodopsin-2, a light-sensitive protein that was fused to yellow fluorescent protein, directly into the BNST via microinjection. The BNST projections are stimulated by exposing them to blue light using specially implanted optical fibers. Since these neurons are GABAeric, they inhibit the postsynaptic LH neurons. This is shown schematically in the figure below.

Fig. 1 (modified from Jennings et al., 2013). VgatBNST→LH circuit activation induces feeding in well-fed mice. (A) Schematic showing VgatBNST→LH circuit targeting.


A different circuit was targeted in control mice, the projection from BNST to the ventral tegmental area (VTA). Activation of the VgatBNST→VTA projection did not induce voracious feeding behavior. But the mice did find it rewarding, which isn't a surprise... the VTA contains the dopaminergic cell bodies of the mesocortical dopamine system.

This is very impressive work in tune with the priorities of the BRAIN Initiative. Unaffiliated expert commenters have noted:

“This is a really important missing piece of the puzzle,” says neuroscientist Seth Blackshaw of Johns Hopkins University in Baltimore. “These are cell types that weren’t even predicted to exist.” A deeper understanding of how the brain orchestrates eating behavior could lead to better treatments for disorders such as anorexia and obesity, he says.

 And this:

Cynthia Bulik, Distinguished Professor of Eating Disorders at UNC School of Medicine and the Gillings School of Global Public Health, says, “Stuber’s work drills down to the precise biological mechanisms that drive binge eating and will lead us away from stigmatizing explanations that invoke blame and a lack of willpower.”

Finally, we have one minor skeptic:

Previous studies from other groups had shown the opposite of what Stuber's team found: when other researchers activated the LH by exposing it to the neurotransmitter glutamate or by electrically stimulating the neurons, animals would start eating. However, B. Glenn Stanley, a professor at UC Riverside who studies the brain mechanisms of eating behavior, said Stuber's team’s results are not necessarily in conflict with earlier findings. “To see an inconsistency would be an oversimplification,” said Stanley.

Stanley noted that Stuber's group focused on a subset of neurons in the LH, those interacting with neurons from the BNST.  ...

It's possible that some areas of the LH stimulate feeding when they're activated, and others when they are inhibited, Berthoud added. “The lateral hypothalamus is really a big area,” he said, adding that the authors didn't describe precisely where those neurons turned off by the BNST reside.

Two weeks ago, the BRAIN Working Group issued its Interim Report (PDF). High priority areas for 2014 include a focus on cell types and circuit manipulation:

#1. Generate a Census of Cell Types. It is within reach to characterize all cell types in the nervous system, and to develop tools to record, mark, and manipulate these precisely defined neurons in vivo. We envision an integrated, systematic census of neuronal and glial cell types, and new genetic and non-genetic tools to deliver genes, proteins, and chemicals to cells of interest. Priority should be given to methods that can be applied to many animal species and even to humans.

#4. Develop A Suite of Tools for Circuit Manipulation. By directly activating and inhibiting populations of neurons, neuroscience is progressing from observation to causation, and much more is possible. To enable the immense potential of circuit manipulation, a new generation of tools for optogenetics, pharmacogenetics, and biochemical and electromagnetic modulation should be developed for use in animals and eventually in human patients. Emphasis should be placed on achieving modulation of circuits in patterns that mimic natural activity.

Translation to Treatments for Human Obesity and Binge Eating Disorders

How close are we to applying this knowledge to treat people with severe intractable obesity? Not very. Optogenetics is a very invasive method. That's why development of new technologies is another high priority area of BRAIN (i.e., "advancing innovative neurotechnologies"). Nevertheless, it's a key component that will advance basic knowledge of neurocircuit functioning.

Has the potential for breakthrough treatments been overblown? Or is it all part of generating enthusiasm and public support (and hence $$)? Jennings et al. refrained from mentioning obesity except in the first and last sentences of their paper. In the press, senior author Garret Stuber said, “The study underscores that obesity and other eating disorders have a neurological basis. With further study, we could figure out how to regulate the activity of cells in a specific region of the brain and develop treatments.”  [i.e., less restrained]

But what are these treatments?? How are they being developed? In its section on Human Neuroscience and Neurotechnology, the BRAIN Report notes that “The study of human brain function faces major challenges because many experimental approaches applicable to laboratory animals cannot be deployed in humans.” They call for improving the resolution and power of human neuroimaging methods, for instance, and learning more about the cellular mechanisms that generate the hemodynamic signal measured by fMRI.

Below I'll list a few more crucial areas where the animal and human studies can inform each other, using the lateral hypothalamus and obesity as illustrations. Then I'll conclude with speculations on integrating multiple levels (and perspectives).


Deep Brain Stimulation

Currently, the most obvious link between circuit manipulation in animals and humans is the increasing number of indications for deep brain stimulation (DBS). And here, pilot studies of DBS for the treatment of obesity have been ongoing for several years (Whiting et al., 2012). Stimulating electrodes were implanted bilaterally in the LH of three patients with refractory obesity. They were enrolled in a two year FDA-approved study on safety after meeting stringent selection criteria: unsuccessful gastric bypass surgery, weighing over 50% more than ideal body weight (BMI ≥ 40), passing physical and psychological examinations. The results were decidedly mixed. One patient lost no weight, and the other two lost only 12.3% and 16.4%. However, this was a study of safety (not efficacy). No undue adverse events were reported, although non-optimal LH stimulation could produce transient sensations of nausea and feeling too hot, while presumed VM stimulation could produce a transient anxiety or panic response.


Detailed Neuroanatomy of Human Hypothalamus

A new MRI atlas of the human hypothalamus was recently published in NeuroImage (Baroncini et al., 2012). Post-mortem histological sections were processed with Nissl staining of cell bodies and Sudan Black B to identify fiber tracts. These were compared to MRI sections and mapped to onto standard Montreal Neurological Institute (MNI) coordinate space. Developing more detailed anatomical atlases is critical for improving localization accuracy in stereotactic neurosurgery, including implantation of DBS electrodes. Perhaps the Hypothalamic Atlas of the future will include details about  gene expression profiles (à la Allen Human Brain Atlas) and cell types within each nucleus.


Animal Models of DBS for Obesity

Studies of DBS have been conducted in rat (Sani et al., 2007) and minipig (Melega et al., 2012) models of obesity.  Continuous bilateral stimulation to inhibit the LH caused relative weight loss in rats, while low frequency stimulation of VM was promising in minipigs. Electrode locations and stimulation parameters can be systematically tested in these animal models.

Göttingen Minipig

Neurology vs. Psychiatry vs. Clinical Psychology (why can't we all just get along?)

I found it striking that Dr. Stuber said his lab's study reinforces the view that obesity and other eating disorders have a neurological basis. Was his comment meant generically, that they have a basis in the brain? Or did he mean these are neurological disorders like epilepsy, Parkinson's disease, and Alzheimer's disease? These diseases are largely unaffected by your outlook on life, and they're not amenable to psychotherapy. How would a neurological definition of binge eating differ from a psychiatric one? That might depend if you're using DSM-5 or a futuristic biologically-based diagnostic scheme. In the U.S., federally funded research at NIMH is moving in a direction consonant with the circuit view presented here, i.e. the Research Domain Criteria (RDoC) framework.

Moving in the opposite direction, the British Psychological Society's Division of Clinical Psychology recently issued a Position Statement on the Classification of Behaviour and Experience in Relation to Functional Psychiatric Diagnoses, which advocated “a paradigm shift in how we understand mental distress towards one which is no longer based on diagnosis and a ‘disease’ model.”  [a rather non-biological view]


Behaviors Don't Exist in a Subcortical Vacuum

Why is it so hard to land somewhere in the middle? What's completely missing from BRAIN is the recognition that social, emotional, and environmental factors can influence the onset of binge eating and other psychiatric disorders in humans. This complicates the utopia of circuit manipulation to cure eating disorders. What are the external factors (e.g., social pressure, stressors, negative evaluation) and internal states (e.g., emotional, cognitive, endocrine) that precipitate the onset (or end) of a binge? Certainly nothing as dramatic as optogenetic activation or inactivation.

The Report pays lip service to the prefrontal cortex and top-down control of behavior (p. 23), but modeling such influences is beyond the scope of the Initiative. But hey! you might say. The plan is ambitious and grandiose enough as it is... you can't even begin to scratch the surface with $100 million in 2014.

But why not push the speculation a bit further? If you're going to anticipate dreaming up entirely new technologies, why not shoot for the stars and identify top-down inputs to BNST neurons?


The Rise of the Circuit-Based Human

Vaughan Bell recently wrote an insightful article about Changing brains: why neuroscience is ending the Prozac era, in which he said:

As the Prozac nation fades, the empire of the circuit-based human will rise, probably to the point where dinner party chatter will include the misplaced jargon of systems neuroscience.

Ironically, Stuber the optogenetics researcher speculated that drug development might be the best and most practical way to go in the future:

Stuber said his group is going to focus on characterizing the cells in the circuit to see “what makes them special.” One appealing direction is to develop pharmacotherapies to tweak the activity of these cells and potentially change feeding behaviors long term.

Irrational Exuberance?

The BRAIN Interim Report presents many reasons for optimism, but it is in part a political document, produced under the auspices of the Obama White House. It proposes a visionary collaborative world of neuroscience research where competition for scarce resources is unknown. It's an idealized blueprint where all the start-up funds aren't spent on establishing an infrastructure. All of these wonderful ideas are to be implemented in fiscal year 2014, which starts tomorrow... if the federal government doesn't shut down, that is.

Even in my Neurocomplimentary guise, I suppose my depressive realism still gets the best of me.


References

Baroncini M, Jissendi P, Balland E, Besson P, Pruvo JP, Francke JP, Dewailly D, Blond S, Prevot V. (2012). MRI atlas of the human hypothalamus. Neuroimage 59(1):168-80.

DELGADO JM & ANAND BK (1953). Increase of food intake induced by electrical stimulation of the lateral hypothalamus. The American journal of physiology, 172 (1), 162-8. PMID: 13030733

Jennings JH, Rizzi G, Stamatakis AM, Ung RL, & Stuber GD (2013). The inhibitory circuit architecture of the lateral hypothalamus orchestrates feeding. Science, 341 (6153), 1517-21. PMID: 24072922

Melega WP, Lacan G, Gorgulho AA, Behnke EJ, De Salles AA. (2012). Hypothalamic deep brain stimulation reduces weight gain in an obesity-animal model. PLoS One 7(1):e30672.

Sani S, Jobe K, Smith A, Kordower JH, Bakay RA.(2007). Deep brain stimulation for treatment of obesity in rats. J Neurosurg. 107(4):809-13.

Whiting DM, Tomycz ND, Bailes J, de Jonge L, Lecoultre V, Wilent B, Alcindor D, Prostko ER, Cheng BC, Angle C, Cantella D, Whiting BB, Mizes JS, Finnis KW, Ravussin E, & Oh MY (2013). Lateral hypothalamic area deep brain stimulation for refractory obesity: a pilot study with preliminary data on safety, body weight, and energy metabolism. Journal of neurosurgery, 119 (1), 56-63. PMID: 23560573

A well fed mouse from the experiment consuming bacon and donuts, despite already having its energy requirements met.  Credit: Josh Jennings.

Remembering the Work of Dr. Patricia Goldman-Rakic

A touching and comprehensive review article in Cerebral Cortex commemorates the life and work of Dr. Patricia Goldman-Rakic on the ten year anniversary of her death (Arnsten, 2013). The author of over 600 publications, Goldman-Rakic worked at NIMH from 1965-1979 and was a professor at Yale from 1979-2003. She served as President of the Society for Neuroscience in 1989-90 and was elected to the National Academy of Sciences in 1990. The review was written by one of her former post-docs, Dr. Amy F.T. Arnsten, herself a professor at Yale.


Keeping a Life "in mind"

Dr. Goldman-Rakic is best known for her research on working memory and the prefrontal cortex (PFC). Working memory is a transient form of memory that actively maintains and manipulates information for brief periods of time (Goldman-Rakic, 1995):

Working memory in its most elementary form, the ability to keep events "in mind" for short periods of time, has been studied in nonhuman primates by delayed-response paradigms. Whereas in humans, facts and events accessed from long-term memory stores can be instigated by verbal instructions, in experiments with animals, the information to be processed has to be provided by the experimenter.

Building on the work of Fuster and colleagues, her studies demonstrated that neurons in the dorsolateral portion of the PFC fire more rapidly when a spatial location cue is removed from the visual field and must be remembered over a brief delay. The sample neuron in the figure below codes for targets located at 270 degrees and not for targets at other locations. Note that the neurons's response is specifically enhanced over the delay period (D).

Fig 1 (modified from Goldman-Rakic, 1995). Neuron during the Many Trials over Which a Monkey Performed an Oculomotor Delayed-Response Working Memory Task. The neuron's response for all trials at the preferred target location is shown as a histogram of the average response per unit time for that location. The activity is also shown in relation to task events (C, cue; D, delay; R, response) on a trial-by-trial basis.


These neurons are located in the dorsal bank of the principal sulcus in monkey dorsolateral PFC, equivalent to Brodmann area 46 in humans. Goldman-Rakic and colleagues conducted extensive neuroanatomical tracing studies in the 1980's to map out the connections of this region and the posterior parietal cortex, major hubs in the brain's larger scheme of visuospatial processing.

Fig. 2 (Arnsten, 2013). The cortical circuitry for spatial cognition, based on the work of Goldman-Rakic and Selemon. Note that both the dlPFC (area 46) and parietal cortex have many shared connections to subcortical structures that are not shown in this illustration, as well as “nonshared” connections that are not included in this diagram {from L. Selemon}.


Goldman-Rakic's work was enormously influential, as shown in the figure below.

Fig. 1 (Arnsten, 2013). Timeline of the discoveries of the PFC role in working memory (WM) and the key contributions of Goldman-Rakic. The graph shows the number of papers cited on PubMed using the search term “prefrontal cortex” for each decade ending in the year noted. Key publications by Goldman-Rakic and other early pioneers are indicated.


Other major areas of research reviewed by Arnsten (2013) include the Key Role of Dopamine and Neuromodulation (e.g., D1 vs. D2 Receptor Actions, the D1 Receptor “inverted-U” Dose–Response), the Neurobiological Foundations of Schizophrenia (e.g., Insults to dlPFC Microcircuitry), and the dlPFC Microcircuits that Generate Mental Representations. The tribute article is open access and can be read freely by all.


A Life of the Mind, Shaped by Working Memory

The significance of working memory for higher cortical function is not necessarily self-evident. Perhaps even the quality of its transient nature misleads us into thinking it is somehow less important than the more permanent archival nature of long-term memory. However, the brain’s working memory function, i.e., the ability to bring to mind events in the absence of direct stimulation, may be its inherently most flexible mechanism and its evolutionarily most significant achievement. Thus, working memory confers the ability to guide behavior by representations of the outside world rather than by immediate stimulation, and thus to base behavior on ideas and thoughts.

- Pat Goldman-Rakic (1991)

References

Arnsten AF (2013). The Neurobiology of Thought: The Groundbreaking Discoveries of Patricia Goldman-Rakic 1937-2003. Cerebral Cortex PMID: 23926115

Goldman-Rakic PS (1995). Cellular basis of working memory. Neuron, 14 (3), 477-85 PMID: 7695894

from Patricia Goldman-Rakic, 1937–2003

A New Slant on Frontal Connectivity: the Frontal Aslant Tract

The frontal aslant tract is shown in yellow (Fig 5, Catani et al., 2012).

It's not every day that you hear about a newly described white matter pathway in the human brain. An interesting new study by a group of researchers in London and Chicago found a novel fiber tract implicated in verbal fluency impairments in patients with a lesser known neurodegenerative illness (Catani et al., 2013).

This short fiber tract connects two different regions in the frontal lobe. It was recently identified using a combination of diffusion imaging and post-mortem dissection (Lawes et al., 2008; Catani et al., 2012; Thiebaut de Schotten et al., 2012). Dubbed the frontal aslant tract (FAT) by Catani and colleagues, it connects the posterior portion of the inferior frontal gyrus (IFG) to the supplementary motor area (SMA) and pre-SMA on the medial wall.¹

A number of experiments have already looked at the functional connectivity of these regions, during both resting state and task activation conditions. Statistically correlated fluctuations in the BOLD signal ² are thought to reflect functional connectivity between two regions, but there is often no evidence that the two regions are directly connected anatomically. Therefore, in vivo structural MRI methods such as diffusion imaging can provide complementary data by visualizing white matter pathways to determine anatomical connections.

The diffusion tractography results were then compared to blunt dissection of tracts from post-mortem brains, which helped to validate a method that some view as prone to limitations and potential artifacts.³

Fig. 10 (modified from Catani et al., 2012). Coronal slices of the ‘Digital Dejerine’ maps ⁴  and post-mortem blunt dissections of the corresponding tracts. E) The frontal aslant tract (FAT) connecting inferior and superior frontal gyri.


A comparative study went further, showing that the results obtained from human tractography compared favorably to axonal tracing methods in monkeys (Thiebaut de Schotten et al., 2012).⁵ 

Fig. 6 (Thiebaut de Schotten et al., 2012). Reconstructions of the frontal aslant tract: comparison between post-mortem axonal tracing in monkey and human in vivo SD [Spherical Deconvolution] tractography shows simian-human similarities.


However, one difference between this tract in monkeys and humans is that the FAT is lateralized in humans, being larger in the left hemisphere than in the right (Catani et al., 2012). In the left hemisphere, posterior IFG is part of Broca's area. This brings us back to the clinical importance of this basic neuoanatomical work.


Verbal Fluency and the Frontal Aslant Tract

Primary progressive aphasia (PPA) is a neurodegenerative disorder, the hallmark of which is the deterioration of specific speech and language functions. There are three variants, each with characteristic behavioral, neuroanatomical, and pathological features (Gorno-Tempini et al., 2011):

• Nonfluent/Agrammatic Variant PPA is characterized by halting, effortful speech with difficulties producing grammatical output and/or comprehending syntactically complex sentences. Word comprehension and object knowledge are intact. Atrophy in the left frontal cortex is apparent on MRI.
• Semantic Variant PPA is marked by impairments that include comprehending the meanings of words, naming objects and understanding their function. Motor speech production and grammatical output are spared. Atrophy is seen in the anterior temporal lobe.
• Logopenic Variant PPA involves word finding problems, phonological speech errors, and difficulties in repeating words and sentences. Word comprehension, object knowledge, and grammar are spared. Degeneration of left posterior temporal-parietal regions is observed.

In the latest study by Catani et al. (2013), 35 patients with PPA and 29 controls participated in behavioral testing and MRI scanning. The tests included standard evaluations of language abilities including the Western Aphasia Battery, the Boston Naming Test, and the Peabody Picture Vocabulary Test. Tractography identified the frontal aslant tract and the uncinate fasciculus, which connects anterior temporal lobe regions to the IFG pars orbitalis and the orbitofrontal cortex. Quantitative measures included the number of streamlines (tract volume), fractional anisotropy, and radial diffusivity (measures of white matter integrity and axonal/myelin damage, respectively).*

Results indicated that patients with Nonfluent/Agrammatic PPA were impaired in a speech production task that required telling the story of Cinderella from a picture book. Poor performance in verbal fluency was associated with the extent of damage in the FAT, but grammatical deficits were not. In contrast, patients with Semantic Variant PPA showed deficits in semantic processing which correlated with degeneration in the uncinate fasciculus.

What are the implications for the neuroanatomy of verbal fluency and speech output?

...Patients with lesions of the pre-supplementary motor area present with various degrees of speech impairment from a total inability to initiate speech (i.e. mutism) to mild altered fluency. Our findings suggest that these medial regions of the frontal lobe could facilitate speech initiation through direct connection to the pars opercularis of the inferior frontal gyrus. Indirect support of this interpretation comes from the frequent observation of impaired fluency in patients with deep lesions in the frontal periventricular white matter. In these cases, a disconnection of the frontal aslant could explain the emergence of symptoms usually associated with frontal cortical damage.

More broadly, characterizing the different patterns of degeneration in these PPA variants of frontotemporal lobar degeneration, their underlying neuropathologies (e.g., tau, ubiquitin/TDP43, or amyloid plaques) and genetic mutations are key areas of research (Gorno-Tempini et al., 2011). Why is the pathology in Semantic PPA preferentially located in anterior temporal regions, while the neuropathological processes in Nonfluent/Agrammatic PPA are drawn to the left frontal cortex? Identifying macro-level structural features such as FAT is extremely important, but the next step is to determine exactly why the frontal aslant tract is targeted.


* ADDENDUM (July 8 2013): as commenter Rob pointed out, "radial diffusivity is most often interpreted as a measure of myelination." I amended the post to reflect what the authors actually said in their paper.


Footnotes

¹ Also known as the frontal operculum, Brodmann area 44 is the posterior portion of the inferior frontal gyrus (i.e., the inferior frontal gyrus pars opercularis). In the left hemisphere, BA44 is part of Broca's area.

² Studies of resting state functional connectivity studies have become an enormously popular way to characterize brain connectivity in health and disease states. We can issue technical caveats all around, including how closely the BOLD signal measures neural activity and how accurately diffusion tractography captures true white matter connections. More on that below.

³ Diffusion imaging is an MRI method that measures the diffusion of water molecules. After using complex mathmatical algorithms and tractography methods, it can be used to visualize white matter pathways. Some potential artifacts are discussed at PractiCal fMRI, and recent advances in advances in diffusion imaging and tractography methods are presented in Pushing the limits of in vivo diffusion MRI for the Human Connectome Project.

⁴ The authors describe how the ‘Digital Dejerine’ maps were constructed (Catani et al., 2012):

Digital Dejerine Maps were obtained by constraining tractography in non-contiguous brain slices of 2 mm (Axial, Sagittal, Coronal). Tractography was started from 10 seed points randomly placed inside each brain voxel and for each fibre orientation. Streamlines were propagated as in the whole brain tractography following fibre orientations using Euler integration with a step size of .5 mm and an angular threshold of 45°. Tractography propagation was arbitrary stopped after 40 mm. This enhances visualization of the white matter bundles that propagate along the plane of the slice selected. Bundles that are oriented perpendicularly to the surface of the slice are visualized only as dots or very short streamlines. Tractography maps were finally visualized using a lookup table empirically tuned to simulate historical black-and-white anatomical drawings.

⁵ Here the authors discuss comparable results from the two methods (Thiebaut de Schotten et al., 2012):

...axonal tracing allows for the identification of single axon trajectories (Schmahmann and Pandya, 2006) and detailed description of their cortical terminations, whereas SD tractography is based on the diffusion signal acquired from relatively large voxels containing multiple axonal bundles, and is limited in reconstructing tracts approaching cortical regions. This methodological difference may account for tracts that were identified in the monkey, but not in the human brain. Despite the above limitations, we show that the majority of frontal lobe connections described in the monkey brain through axonal tracing, can be also visualised in the human brain using SD tractography.

References

Catani M, Dell'acqua F, Vergani F, Malik F, Hodge H, Roy P, Valabregue R, & Thiebaut de Schotten M (2012). Short frontal lobe connections of the human brain. Cortex 48 (2), 273-91 PMID: 22209688

Catani M, Mesulam MM, Jakobsen E, Malik F, Matersteck A, Wieneke C, Thompson CK, Thiebaut de Schotten M, Dell'acqua F, Weintraub S, & Rogalski E (2013). A novel frontal pathway underlies verbal fluency in primary progressive aphasia. Brain PMID: 23820597

Gorno-Tempini ML, Hillis AE, Weintraub S, Kertesz A, Mendez M, Cappa SF, Ogar JM, Rohrer JD, Black S, Boeve BF, Manes F, Dronkers NF, Vandenberghe R, Rascovsky K, Patterson K, Miller BL, Knopman DS, Hodges JR, Mesulam MM, & Grossman M (2011). Classification of primary progressive aphasia and its variants. Neurology, 76 (11), 1006-14 PMID: 21325651

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What is this, anyway?

The Neurocomplimenter is a new project designed to counter gratuitous anti-neuroscience sentiment.  It’s part of my campaign to combat pop neurobashing profiteers.

The Neurocomplimenter

It’s here!

I’m starting a backlash against the fashionable anti-neuro backlash. I’m tired of the relentless assaults on some cartoon version of neuroscience, and having our own critiques of specific studies, faulty statistical practices, and glitzy media coverage used against us. After over seven years of critical neuroblogging, it’s time to highlight the positives: meet The Neurocomplimenter.

"That was a fantastic study! Good show!"

The project started with two inaugural posts hosted at a different locale:

• Helicopter controlled by human EEG 

• The End of Language Embodiment

From now on, the occasional neurocomplimentary pieces will appear on this site.
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