Monday, May 21, 2018

What counts as "memory" and who gets to define it?


Do Plants Have “Memory”?


A new paper by Bédécarrats et al. (2018) is the latest entry into the iconoclastic hullabaloo claiming a non-synaptic basis for learning and memory. In short, “RNA extracted from the central nervous system of Aplysia given long-term sensitization training induced sensitization when injected into untrained animals...” The results support the minority view that long-term memory is not encoded by synaptic strength, according to the authors, but instead by molecules inside cells (à la Randy Gallistel).

Adam Calhoun has a nice summary of the paper at Neuroecology:
...there is a particular reflex 1 (memory) that changes when they [Aplysia] have experienced a lot of shocks. How memory is encoded is a bit debated but one strongly-supported mechanism (especially in these snails) is that there are changes in the amount of particular proteins that are expressed in some neurons. These proteins might make more of one channel or receptor that makes it more or less likely to respond to signals from other neurons. So for instance, when a snail receives its first shock a neuron responds and it withdraws its gills. Over time, each shock builds up more proteins that make the neuron respond more and more. These proteins are built up by the amount of RNA (the “blueprint” for the proteins, if you will) that are located in the vicinity of the neuron that can receive this information.  ...

This new paper shows that in these snails, you can just dump the RNA on these neurons from someone else and the RNA has already encoded something about the type of protein it will produce.

Neuroskeptic has a more contentious take on the study, casting doubt on the notion that sensitization of a simple reflex to any noxious stimulus (a form of non-associative “learning”) produces “memories” as we typically think of them. But senior author Dr. David Glanzman tolerated none of this, and expressed strong disagreement in the comments:
“I’m afraid you have a fundamental misconception of what memory is. We claim that our experiments demonstrate transfer of the memory—or essential components of the memory—for sensitization. Now, although sensitization may not comport with the common notion of memory—it’s not like the memory of my Midwestern grandmother’s superb blueberry pies, for example—it nevertheless has unambiguous status as memory.  ...  [didactic lesson continues] ...  We do not claim in our paper that declarative memories—such as my memory of my grandmother’s blueberry pies—or even simpler forms of associative memories like those induced during classical conditioning—can be transferred by RNA. That remains to be seen.”

OK, so Glanzman gets to define what memory is. But later on he's caught in a trap and has to admit:
“Of course, there are many phenomena that can be loosely regarded as memory—the crease in folded paper, for example, can be said to represent the memory of a physical action.”

That was in response to who said:
“So a transfer of RNA that activates a cellular mechanism associated with touch isn't memory, but rather just exogenously turning on a cellular pathway. By that logic, gene therapy to treat sickle cell anemia changes blood "memory".”2

However, my favorite comment was from Smut Clyde:
“Kandel set the precedent that reflexes in Aplysia are "memories", and now we're stuck with it.”

This reminded me of Dr. Kandel's bold [outlandish?] attempt to link psychoanalysis, Aplysia withdrawal reflexes, and human anxiety (Kandel, 1983). I was a bit flabbergasted that gill withdrawal in a sea slug was considered “mentation” (thought) and could support Freudian views.3
In the past, ascribing a particular behavioral feature to an unobservable mental process essentially excluded the problem from direct biological study because the complexity of the brain posed a barrier to any complementary biological analysis. But the nervous systems of invertebrates are quite accessible to a cellular analysis of behavior, including certain internal representations of environmental experiences that can now be explored in detail; This encourages the belief that elements of cognitive mentation relevant to humans and related to psychoanalytic theory can be explored directly [in Aplysia] and need no longer be merely inferred.

- click on image for a larger view -



So anticipatory anxiety in humans is isomorphic to invertebrate responses in a classical aversive conditioning paradigm, and chronic anxiety is recreated by long-term sensitization paradigms. Perhaps I missed the translational advances here, and any application to Psychoanalytic and Neuropsychoanalytic practice that has been fully realized.

If we want to accept a flexible definition of learning and memory in animals, why not consider associative learning experiments in pea plants, where a neutral cue predicting the location of a light source had a greater effect on the direction of plant growth than innate phototropism (Gagliano et al., 2016)? Or review the literature on associative and non-associative learning in Mimosa? (Abramson & Chicas-Mosier, 2016). Or evaluate the field of ‘plant neurobiology’ and even the ‘Philosophy of Plant Neurobiology’ (Calvo, 2016). Or are the possibilities of chloroplast-based consciousness and “mentation” without neurons too threatening (or too fringe)?

But in the end, we know we've reach peak plant cognition when a predictive coding model appears — Predicting green: really radical (plant) predictive processing (Calvo & Friston, 2017).


Further Reading

The Big Ideas in Cognitive Neuroscience, Explained (especially the sections on Gallistel and Ryan)

What are the Big Ideas in Cognitive Neuroscience? (you can watch the videos of their 2017 CNS talks)


Footnotes

1 edited to indicate my emphasis on reflex more specifically, the gill withdrawal reflex in Aplysia which can only go so far as a model of other forms of memory, in my view.

Another skeptic (but for different reasons) is Dr. Tomás Ryan, who was paraphrased in Scientific American:
But [Ryan] doesn’t think the behavior of the snails, or the cells, proves that RNA is transferring memories. He said he doesn’t understand how RNA, which works on a time scale of minutes to hours, could be causing memory recall that is almost instantaneous, or how RNA could connect numerous parts of the brain, like the auditory and visual systems, that are involved in more complex memories.

3 But I haven't won the Nobel Prize, so what do I know?


References

Abramson CI, Chicas-Mosier AM. (2016). Learning in plants: lessons from Mimosa pudica. Frontiers in psychology Mar 31;7:417.

Bédécarrats A, Chen S, Pearce K, Cai D, Glanzman DL. (2018). RNA from Trained Aplysia Can Induce an Epigenetic Engram for Long-Term Sensitization in Untrained Aplysia. eNeuro. May 14:ENEURO-0038.

Calvo P. (2016). The philosophy of plant neurobiology: a manifesto. Synthese 193(5):1323-43.

Calvo P, Friston K. Predicting green: really radical (plant) predictive processing. Journal of The Royal Society Interface. 14(131):20170096.

Gagliano M, Vyazovskiy VV, Borbély AA, Grimonprez M, Depczynski M. (2016). Learning by association in plants. Scientific Reports Dec 2;6:38427.

Kandel ER. (1983). From metapsychology to molecular biology: explorations into the nature of anxiety. Am J Psychiatry 140(10):1277-93.

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Sunday, May 13, 2018

“My family say they grieve for the old me” – profound personality changes after deep brain stimulation



Deep brain stimulation (DBS) of the subthalamic nucleus in Parkinson's disease (PD) has been highly successful in controlling the motor symptoms of this disorder, which include tremor, slowed movement (akinesia), and muscle stiffness or rigidity. The figure above shows the electrode implantation procedure for PD, where a stimulating electrode is placed in either the subthalamic nucleus, (STN), a tiny collection of neurons within the basal ganglia circuit, or in the internal segment of the globus pallidus, another structure in the basal ganglia (Okun, 2012). DBS of the STN is more common, and more often a source of disturbing non-motor side effects.

In brief, DBS of the STN alters neural activity patterns in complex cortico-basal-ganglia-thalamo-cortical networks (McIntyre & Hahn, 2010).

DBS surgery may be recommended for some patients in whom dopamine (DA) replacement therapy has become ineffective, usually after a few years. DA medications include the classic DA precursor L-DOPA, followed by DA agonists such as pramipexole, ropinirole, and bromocriptine. But unfortunately, impulse control disorders (ICDs, e.g., compulsive shopping, excessive gambling, binge eating, and compulsive sexual behavior) occur in about 17% of PD patients on DA agonists (Voon et al., 2017).

There are many first-person accounts from PD patients who describe uncharacteristic and embarrassing behavior after taking DA agonists, like this grandpa who started seeing prostitutes for the first time in his life:
'I have become an embarrassment'

For most of his life John Smithers was a respected family man who ran a successful business. Then he started paying for sex. Now, in his 70s, he explains how his behaviour has left him broke, alone and tormented

I am 70 years old and used to be respectable. I was a magistrate for 25 years, and worked hard to feed my children and build up the family business. I was not the most faithful of husbands, but I tried to be discreet about my affairs.1 Now I seem to be a liability. Over the last two decades I have spent a fortune on prostitutes and lost two wives. I have made irrational business decisions that took me to the point of bankruptcy. I have become an embarrassment to my nearest and dearest.

Also reports like: Drug 'led patients to gamble'.


New-onset ICDs can also occur in patients receiving STN DBS, but the effects are mixed across the entire population: ICD symptoms can also improve or remain unchanged. Why this is the case is a vexing problem that includes premorbid personality, genetics, family history, past and present addictions, and demographic factors (Weintraub & Claassen).


- click on image for a larger view -



Neuroethicists are weighing in on the potential side effects of DBS that may alter a patient's perception of identity and self. A recent paper included a first-person account of altered personality and a sense of self-estrangement in a 46 year old woman undergoing STN DBS for PD (Gilbert & Viaña, 2018):
The patient reported a persistent state of self-perceived changes following implantation. More than one year after surgery, her narratives explicitly refer to a persistent perception of strangeness and alteration of her concept of self. For instance, she reported:
"can't be the real me anymore—I can't pretend . . . I think that I felt that the person that I have been [since the intervention] was somehow observing somebody else, but it wasn't me. . . . I feel like I am who I am now. But it's not the me that went into the surgery that time. . . . My family say they grieve for the old [me]. . . ."

Many of her quotes are striking in their similarity to behaviors that occur in the manic phase of bipolar disorder {loss of control, grandiosity}:
The patient also reported developing severe postoperative impulsivity: "I cannot control the impulse to go off if I'm angry." In parallel, while describing a sense of loss of control over some impulsions, she has also recognized that DBS gave her increased feelings of strength: "I never had felt this lack of power or this giving of power—until I had deep brain stimulation."

{also uncharacteristic sexual urges and hypersexuality; excessively energetic; compulsive shopping}:
...she experienced radically enhanced capacities, in the form of increased uncontrollable sexual urges:
"I know this is a bit embarrassing. But I had 35 staples in my head, and we made love in the hospital bathroom and that wasn't just me. It was just I had felt more sexual with the surgery than without."
And greater physical energy:
"I remember about a week after the surgery, I still had the 35 staples in my head and I was just starting to enter the cooler months of winter but my kids had got me winter clothes so I had nothing to wear to the follow up appointment and when I went back there of the morning, I thought "I can walk into the doctor's" even though it was 5 kilometers into town. It's like the psychologist said: "For a woman who had a very invasive brain surgery 9 days ago and you've just almost walked 10 kilometers." And on the way, I stopped and bought a very uncharacteristic dress, backless—completely different to what I usually do."

Examining the DSM-5 criteria for bipolar mania, it seems clear (to me, at least) that the patient is indeed having a prolonged manic episode induced by STN DBS.
In order for a manic episode to be diagnosed, three (3) or more of the following symptoms must be present:
  • Inflated self-esteem or grandiosity
  • Decreased need for sleep (e.g., one feels rested after only 3 hours of sleep)
  • More talkative than usual or pressure to keep talking
  • Flight of ideas or subjective experience that thoughts are racing
  • Attention is easily drawn to unimportant or irrelevant items
  • Increase in goal-directed activity (either socially, at work or school; or sexually) or psychomotor agitation
  • Excessive involvement in pleasurable activities that have a high potential for painful consequences (e.g., engaging in unrestrained buying sprees, sexual indiscretions, or foolish business investments)

It's also notable that she divorced her husband, moved to another state, ruptured the therapeutic relationship with her neurologist and surgical team, and made a suicide attempt. She also took up painting and perceived the world in a more vibrant, colorful way {which resembles narratives of persons experiencing manic episodes}:
"I don't know, all the senses came alive. I wanted to listen to Paul Kelly and all of my favorite music really loud in the toilet. And you know, also everything was colourful. . . . Well, since brain surgery I can. I didn't bother before. I can see the light . . . the light that is underlying every masterpiece in photography. . . . I've seen it like I've never seen it before . . . I am a totally different person. I like it that I love photography and music and colourful clothes, but where is the old me now?"

However, she appears to display more insight into her altered behavior than {most} people in the midst of bipolar mania. Perhaps her reality monitoring abilities are more intact? Or it's because her symptoms wax and wane.2 But like in many manic individuals, she did not want this feeling to stop:
"I went to the psychiatrist, and he said, 'Right, well, this is bordering on mania [NOTE: that is an understatement], you need to turn the settings right down to manage it.' I said to him, 'Please don't, this is not over the top—this is just joy.' "

I think this line of research studying individuals with Parkinson's who have impulse control disorders due to DA replacement or DBS   can provide insight into bipolar mania. Certainly, drugs that act as antagonists at multiple DA receptor subtypes (typical and atypical antipsychotics) are used in the management of bipolar disorder.

Patient narratives are also informative in this regard, and provide critical information for individuals considering various types of therapies for PD. In this paper, the patient was not informed by the medical team that there could be undesirable psychiatric side effects. She has taken legal action against the lead neurosurgeon, and the proceedings were ongoing when the article was written.


ADDENDUM (May 14 2018): The study was conducted in accordance with Human Research Ethics Committee regulations. The patient provided consent to have her narratives included in publications on neuropsychiatric side effects of DBS for PD.


Footnotes

1 One might wonder whether Mr. Smithers' premorbid propensity for affairs made him more vulnerable for compulsive sexual activity after DA agonists. And that is one consideration displayed in the box and circle diagram above.

2 She did experience bouts of depression as well as mania, perhaps related to the stimulation parameters and precise location. And bipolar individuals also gain insight once the manic episode subsides.


References

Gilbert F, Viaña JN. (2018). A Personal Narrative on Living and Dealing with Psychiatric Symptoms after DBS Surgery. Narrat Inq Bioeth. 8(1):67-77.

McIntyre CC, Hahn PJ. (2010). Network perspectives on the mechanisms of deep brain stimulation. Neurobiol Dis. 38(3):329-37.

Voon V, Napier TC, Frank MJ, Sgambato-Faure V, Grace AA, Rodriguez-Oroz M, Obeso J, Bezard E, Fernagut PO. (2017). Impulse control disorders and levodopa-induceddyskinesias in Parkinson's disease: an updateLancet Neurol. 16(3):238-250.

Weintraub D, Claassen DO. (2017). Impulse Control and Related Disorders in Parkinson's Disease. Int Rev Neurobiol. 133:679-717.

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Sunday, April 29, 2018

The Fractionation of Auditory Semantic Knowledge: Agnosia for Bird Calls




How is semantic knowledge represented and stored in the brain? A classic way of addressing this question is via single-case studies of patients with brain lesions that lead to a unique pattern of deficits. Agnosia is the inability to recognize some class (or classes) of entities such as objects or persons. Agnosia in the visual modality is most widely studied, but agnosias in the auditory and olfactory modalities have been reported as well. A key element is that basic sensory processing is intact, but higher-order recognition of complex entities is impaired.

Agnosias that are specific for items in a particular category (e.g., animals, fruits/vegetables, tools, etc.) are sometimes observed. An ongoing debate posits that some category-specific dissociations may fall out along sensory/functional lines (the Warrington view), or along domain-specific lines (the Caramazza view).1 The former suggests that knowledge of living things is more reliant on vision (you don't pick up and use an alligator), while knowledge of tools is more reliant on how you use them. The latter hypothesis suggests that evolutionary pressures led to distinct neural systems for processing different categories of objects.2

Much less work has examined how nonverbal auditory knowledge is represented in the brain. A new paper reports on a novel category-specific deficit in an expert bird-watcher who developed semantic dementia (Muhammed et al., 2018). Patient BA lost the ability to identify birds by their songs, but not by their appearance. As explained by the authors:
BA is a dedicated amateur birder with some 30 years’ experience, including around 10 weeks each spring spent in birdwatching expeditions and over the years had also regularly attended courses in bird call recognition, visual identification and bird behaviour. He had extensive exposure to a range of bird species representing all major regions and habitats of the British Isles. He had noted waning of his ability to name birds or identify them from their calls over a similar timeframe to his evolving difficulty with general vocabulary. At the time of assessment, he was also becoming less competent at identifying birds visually but he continued to enjoy recognising and feeding the birds that visited his garden. There had been no suggestion of any difficulty recognising familiar faces or household items nor any difficulty recognising the voices of telephone callers or everyday noises. There had been no evident change in BA's appreciation of music.

BA's brain showed a pattern of degeneration characteristic of semantic dementia, with asymmetric atrophy affecting the anterior, medial, and inferior temporal lobes, to a greater extent in the left hemisphere.



Fig. 1 (modified from Muhammed et al., 2018). Note that L side of brain shown on R side of scan. Coronal sections of BA's T1-weighted volumetric brain MRI through (A) temporal poles; (B) mid-anterior temporal lobes; and (C) temporo-parietal junctional zones. There is more severe involvement of the left temporal lobe.



The authors developed a specialized test of bird knowledge in the auditory, visual, and verbal modalities. The performance of BA was compared to that of three birders similar in age and experience.


Results indicated that “BA performed below the control range for bird knowledge derived from calls and names but within the control range for knowledge derived from appearance.” There was a complicated pattern of results for his knowledge of specific semantic characteristics in the different modalities, but the basic finding suggested an agnosia for bird calls. Interestingly, he performed as well as controls on tests of famous voices and famous face pictures.

Thus, the findings suggest separate auditory and visual routes to avian conceptual knowledge, at least in this expert birder. Also fascinating was the preservation of famous person identification via voice and image. The authors conclude with a ringing endorsement of single case studies in neuropsychology:
This analysis transcends the effects of acquired expertise and illustrates how single case experiments that address apparently idiosyncratic phenomena can illuminate neuropsychological processes of more general relevance.

link via @utafrith


References

Caramazza A, Mahon BZ. (2003). The organization of conceptual knowledge: the evidence from category-specific semantic deficits. Trends Cogn Sci. 7(8):354-361.

Muhammed L, Hardy CJD, Russell LL, Marshall CR, Clark CN, Bond RL, Warrington EK, Warren JD. (2018). Agnosia for bird calls. Neuropsychologia 113:61-67.

Warrington EK, McCarthy RA. (1994). Multiple meaning systems in the brain: a case for visual semantics. Neuropsychologia 32(12):1465-73.

Warrington EK, Shallice T. (1984). Category specific semantic impairments. Brain 107(Pt 3):829-54.


Footnotes

1 I'm using this nomenclature as a shorthand, obviously, as many more researchers have been involved in these studies. And this is an oversimplification based on the origins of the debate.

2 In fact, the always-argumentative Prof. Caramazza gave a lecture on The Representation of Objects in the Brain: Nature or Nurture for winning the Fred Kavli Distinguished Career Contributions in Cognitive Neuroscience Award (#CNS2018). Expert live-tweeter @vukovicnikola captured the following series of slides, which summarizes the debate as resolved in Caramazza's favor (to no one's surprise).







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Saturday, April 07, 2018

Big Theory, Big Data, and Big Worries in Cognitive Neuroscience


Eve Marder, Alona Fyshe, Jack Gallant, David Poeppel, Gary Marcus
image by @jonasobleser

UPDATE April 9 2018: Video of the entire debate is now available at the CNS blogYouTube, and the end of this post.


What Will Solve the Big Problems in Cognitive Neuroscience?

That was the question posed in the Special Symposium moderated by David Poeppel at the Boston Sheraton (co-sponsored by the Cognitive Neuroscience Society and the Max-Planck-Society). The format was four talks by prominent experts in (1) the complexity of neural circuits and neuromodulation in invertebrates; (2) computational linguistics and machine learning; (3) human neuroimaging/the next wave in cognitive and computational neuroscience; and (4) language learning/AI contrarianism. These were followed by a lively panel discussion and a Q&A session with the audience. What a great format!


We already knew the general answer before anyone started speaking.


But I believe that Dr. Eve Marder, the first speaker, posed the greatest challenges to the field of cognitive neuroscience, objections that went mostly unaddressed by the other speakers. Her talk was a treasure trove of quotable witticisms (paraphrased):
  • How much ambiguity can you live with in your attempt to understand the brain? For me I get uncomfortable with anything more than 100 neurons
  • If you're looking for optimization (in [biological] neural networks), YOU ARE DELUSIONAL!
  • Degenerate mechanisms produce the same changes in behavior, even in a 5 neuron network...
  • ..so Cognitive Neuroscientists should be VERY WORRIED


Dr. Marder started her talk by expressing puzzlement about why she would be asked to speak on such a panel, but she gamely agreed. She initially expressed some ideas that almost everyone endorses:
  • Good connectivity data is essential
  • Simultaneous recordings from many neurons is a good idea [but how many is enough?]
But then she turned to the nightmare of trying to understand large-scale brain networks, as is the fashion these days in human fMRI and connectivity studies.
  • It's not clear what changes when circuits get big
  • Assuming a “return to baseline” is always hiding a change that can be cryptic
  • On the optimization issue... nervous systems can't optimize for one situation if it makes them unable to deal with other [unexpected] situations.
  • How does degeneracy relieve the tyranny?
No one knows...

Dr. Marder was also a speaker at the Canonical Computation in Brains and Machines meeting in mid-March (h/t @neuroecology), and her talk from that conference is available online.

I believe the talks from the present symposium will be on the CNS YouTube channel as well, and I'll update the post if/when that happens.

Speaking of canonical computation, now I know why Gary Marcus was apoplectic at the thought of “one canonical cortical circuit to rule them all.” More on that in a moment...


The next speaker was Dr. Alona Fyshe, who spoke about computational vision. MLE, MAP, ImageNet, CNNs. I'm afraid I can't enlighten you here. Like everyone else, she thought theory vs. data is a false dichotomy. Her memorable tag line was “Kill Your Darlings.” At first I thought this meant delete your best line [of code? of your paper?], but in reality “our theories need to be flexible enough to adapt to data” (always follow @vukovicnikola #cns2018 for the best real-time conference coverage).


Next up was Dr. Gary Marcus, who started out endorsing the famous Jonas and Kording (2017) paper Could a Neuroscientist Understand a Microprocessor? which suggested that current data analysis methods in neuroscience are inadequate for producing a true understanding of the brain. Later, during the discussion, Dr. Jack Gallant quipped that the title of that paper should have been “Neuroscience is Hard” (on Twitter, @KordingLab thought this was unfair). For that matter, Gallant told Marcus, “I think you just don't like the brain.” [Gallant is big on data, but not mindlessly]



image via @vukovicnikola


This sparked a lively debate during the panel discussion and the Q&A.


Anyway, back to Marcus. “Parsimony is a false god,” he said. I've long agreed with this sentiment, especially when it comes to the brain the simplest explanation isn't always true. Marcus is pessimistic that deep learning will lead to great advances in explaining neural systems (or AI). It's that pesky canonical computation again. The cerebral cortex (and the computations it performs) isn't uniform across regions (Marcus et al., 2014).

This is not a new idea. In my ancient dissertation, I cited Swindale (1990) and said:
Swindale (1990) argues that the idea of mini-columns and macro-columns was drawn on insufficient data. Instead, the diversity of cell types in different cortical areas may result in more varied and complex organization schemes which would adequately reflect the different types of information stored there [updated version would be “types of computations performed there”].1

Finally, Dr. Jack Gallant came out of the gate saying the entire debate is silly, and that we need both theory and data. But he also thinks it's silly that we'll get there with theory alone. We need to build better measurement tools, stop faulty analysis practices, and develop improved experimental paradigms. He clearly favors the collection of more data, but in a refined way. For the moment, collect large rich naturalistic data sets using existing technology.

And remember, kids, “the brain is a horror show of maps.”



 image via @vukovicnikola



Big Data AND Big Theory: Everyone Agrees (sorta)

Eve Marder – The Important of the Small for Understanding the Big

Alona Fyshe – Data Driven Everything

Gary Marcus – Neuroscience, Deep Learning, and the Urgent Need for an Enriched Set of Computational Primitives

Jack Gallant – Which Presents the Biggest Obstacle to Advances in Cognitive Neuroscience Today: Lack of Theory or Lack of Data?



Gary Marcus talking over Jack Gallant. Eve Marder is out of the frame.
image by @CogNeuroNews


Footnote

1 Another quote from the young Neurocritic:
As finer analyses are applied to both local circuitry and network properties, our theoretical understanding of neocortical operation may require further revision, if not total replacement with other metaphors. At our current state of knowledge, a number of different conceptual frameworks can be overlaid on the existing data to derive an order that may not be there. Or conversely, the data can be made to fit into one's larger theoretical view.



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Saturday, March 31, 2018

Automatically-Triggered Brain Stimulation during Encoding Improves Verbal Recall

Fig. 4 (modified from Ezzyat et al., 2018). Stimulation targets showing numerical increase/decrease in free recall performance are shown in red/blue. Memory-enhancing sites clustered in the middle portion of the left middle temporal gyrus.


Everyone forgets. As we grow older or have a brain injury or a stroke or develop a neurodegenerative disease, we forget much more often. Is there a technological intervention that can help us remember? That is the $50 million dollar question funded by DARPA's Restoring Active Memory (RAM) Program, which has focused on intracranial electrodes implanted in epilepsy patients to monitor seizure activity.

Led by Michael Kahana's group at the University of Pennsylvania and including nine other universities, agencies, and companies, this Big Science project is trying to establish a “closed-loop” system that records brain activity and stimulates appropriate regions when a state indicative of poor memory function is detected (Ezzyat et al., 2018).

Initial “open-loop” efforts targeting medial temporal lobe memory structures (entorhinal cortex, hippocampus) were unsuccessful (Jacobs et al., 2016). In fact, direct electrical stimulation of these regions during encoding of spatial and verbal information actually impaired memory performance, unlike an initial smaller study (Suthana et al., 2012).1

{See Bad news for DARPA's RAM program: Electrical Stimulation of Entorhinal Region Impairs Memory}


However, during the recent CNS symposium on Memory Modulation via Direct Brain Stimulation in Humans, Dr. Suthana suggested that “Stimulation of entorhinal white matter and not nearby gray matter was effective in improving hippocampal-dependent memory...” 2

{see this ScienceNews story}


Enter the Lateral Temporal Cortex

Meanwhile, the Penn group and their collaborators moved to a different target region, which was also discussed in the CNS 2018 symposium: “Closed-loop stimulation of temporal cortex rescues functional networks and improves memory” (based on Ezzyat et al., 2018).


Fig. 4 (modified from Ezzyat et al., 2018). Horizontal section. Stimulation targets showing numerical increase/decrease in free recall performance are shown in red/blue. Memory-enhancing sites clustered in the middle portion of the left middle temporal gyrus.


Twenty-five patients performed a memory task in which they were shown a list of 12 nouns, followed by a distractor task, and finally a free recall phase, where they were asked to remember as many of the words as they could. The participants went through a total of 25 rounds of this study-test procedure.


Meanwhile, the first three rounds were “record-only” sessions, where the investigators developed a classifier a pattern of brain activity that could predict whether or not the patient would recall the word at better than chance (AUC = 0.61, where chance =.50).” 3 The classifier relied on activity across all electrodes that were placed in an individual patient.


Memory blocks #4-25 alternated between Simulation (Stim) and No Stimulation (NoStim) lists. In Stim blocks, 0.5-2.25 mA stimulation was delivered for 500 ms when the classifier AUC predicted 0.5 recall during word presentation. In NoStim lists, stimulation was not delivered on analogous trials, and the comparison between those two conditions comprised the main contrast shown below.


Fig. 3a (modified from Ezzyat et al., 2018). Stimulation delivered to lateral temporal cortex targets increased the probability of recall compared to matched unstimulated words in the same subject (P < 0.05) and stimulation delivered to Non-lateral temporal targets in an independent group (P < 0.01).


The authors found that that lateral temporal cortex stimulation increased the relative probability of item recall by 15% (using a log-binomial model to estimate the relative change in recall probability). {But if you want to see all of the data, peruse the Appendix below. Overall recall isn't that great...}

Lateral temporal cortex (n=18) meant MTG, STG, and IFG (mostly on the left). Non-lateral temporal cortex (n=11) meant elsewhere (see Appendix below). The improvements were greatest with stimulation in the middle portion of the left middle temporal gyrus. There are many reason for poor encoding, and one could be that subjects were not paying enough attention. The authors didn't have the electrode coverage to test that explicitly. This leads me to believe that electrical stimulation was enhancing the semantic encoding of the words. The MTG is thought to be critical for semantic representations and language comprehension in general (Turken & Dronkers, 2011).

Thus, my interpretation of the results is that stimulation may have boosted semantic encoding of the words, given the nature of the stimuli (words, obviously), the left lateralization with a focus in MTG, and the lack of an encoding task. The verbal memory literature clearly demonstrates that when subjects have a deep semantic encoding task (e.g., living/non-living decision), compared to shallow orthographic (are there letters that extend above/below?) or phonological tasks, recall and recognition are improved. Which led me to ask some questions, and one of the authors kindly replied (Dan Rizzuto, personal communication). 4

  1. Did you ever have conditions that contrasted different encoding tasks? Here I meant to ask about semantic vs orthographic encoding (because the instructions were always to “remember the words” with no specific encoding task).
    •  
    • We studied three verbal learning tasks (uncategorized free recall, categorized free recall, paired associates learning) and one spatial navigation task during the DARPA RAM project. We were able to successfully decode recalled / non-recalled words using the same classifier across the three different verbal memory tasks, but we never got sufficient paired associates data to determine whether we could reliably increase memory performance on this task.
     
  2. Did you ever test nonverbal stimuli (not nameable pictures, which have a verbal code), but visual-spatial stimuli? Here I was trying to assess the lexical-semantic nature of the effect. 
    •  
    • With regard to the spatial navigation task, we did observe a few individual patients with LTC stimulation-related enhancement, but we haven't yet replicated the effect across the population.

Although this method may have therapeutic implications in the future, at present it is too impractical, and the gains were quite small. Nonetheless, it is an accomplished piece of work to demonstrate closed-loop memory enhancement in humans.


Footnotes

1 Since that time, however, the UCLA group has reported that theta-burst microstimulation of....
....the right entorhinal area during learning significantly improved subsequent memory specificity for novel portraits; participants were able both to recognize previously-viewed photos and reject similar lures. These results suggest that microstimulation with physiologic level currents—a radical departure from commonly used deep brain stimulation protocols—is sufficient to modulate human behavior and provides an avenue for refined interrogation of the circuits involved in human memory.

2 Unfortunately, I was running between two sessions and missed that particular talk.

3 This level of prediction is more like a proof of concept and would not be clinically acceptable at this point.

4 Thanks also to Youssef Ezzyat and Cory Inman, whom I met at the symposium.


References

Ezzyat Y, Wanda PA, Levy DF, Kadel A, Aka A, Pedisich I, Sperling MR, Sharan AD, Lega BC, Burks A, Gross RE, Inman CS, Jobst BC, Gorenstein MA, Davis KA, Worrell GA, Kucewicz MT, Stein JM, Gorniak R, Das SR, Rizzuto DS, Kahana MJ. (2018). Closed-loop stimulation of temporal cortex rescues functional networks and improves memory. Nat Commun. 9(1): 365.

Jacobs, J., Miller, J., Lee, S., Coffey, T., Watrous, A., Sperling, M., Sharan, A., Worrell, G., Berry, B., Lega, B., Jobst, B., Davis, K., Gross, R., Sheth, S., Ezzyat, Y., Das, S., Stein, J., Gorniak, R., Kahana, M., & Rizzuto, D. (2016). Direct Electrical Stimulation of the Human Entorhinal Region and Hippocampus Impairs Memory. Neuron 92(5): 983-990.

Suthana, N., Haneef, Z., Stern, J., Mukamel, R., Behnke, E., Knowlton, B., & Fried, I. (2012). Memory Enhancement and Deep-Brain Stimulation of the Entorhinal Area. New England Journal of Medicine 366(6): 502-510.

Titiz AS, Hill MRH, Mankin EA, M Aghajan Z, Eliashiv D, Tchemodanov N, Maoz U, Stern J, Tran ME, Schuette P, Behnke E, Suthana NA, Fried I. (2017). Theta-burstmicrostimulation in the human entorhinal area improves memory specificity. Elife Oct 24;6.

Turken AU, Dronkers NF. (2011). The neural architecture of the language comprehension network: converging evidence from lesion and connectivity analyses. Front Syst Neurosci. Feb 10;5:1.


Appendix (modified from Supplementary Table 1)  

- click on image for a larger view - 



In the table above, Stim and NoStim recall percentages are for ALL words in the blocks. But:
  • Only half of the words in each Stim list were stimulated, however, so this comparison is conservative. The numbers improve slightly if you compare just the stimulated words with the matched non-stimulated words. Not all subjects exhibited a significant within-subject effect, but the effect is reliable across the population (Figure 3a)

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Friday, March 23, 2018

25 Years of Cognitive Neuroscience in Boston



The 25th Annual Meeting of the Cognitive Neuroscience Society starts off with a big bang on Saturday afternoon with the Big Theory versus Big Data Debate, moderated by David Poeppel.1


Big Theory versus Big Data: What Will Solve the Big Problems in Cognitive Neuroscience?


My non-commital answers are:

(1) Both.

(2) It depends. (on what you want to do: predict behavior2 (or some mental state), explain behavior, control behavior, etc.)

Abstract: All areas of the sciences are excited about the innovative new ways in which data can be acquired and analyzed. In the neurosciences, there exists a veritable orgy of data – but is that what we need? Will the colossal datasets we now enjoy solve the questions we seek to answer, or do we need more ‘big theory’ to provide the necessary intellectual infrastructure? Four leading researchers, with expertise in neurophysiology, neuroimaging, artificial intelligence, language, and computation will debate these big questions, arguing for what steps are most likely to pay off and yield substantive new explanatory insight.


Talk 1: Eve Marder The Important of the Small for Understanding the Big

Talk 2: Jack Gallant Which Presents the Biggest Obstacle to Advances in Cognitive Neuroscience Today: Lack of Theory or Lack of Data?

Talk 3: Alona Fyshe Data Driven Everything

Talk 4: Gary Marcus Neuroscience, Deep Learning, and the Urgent Need for an Enriched Set of Computational Primitives


Levels of analysis! Marr! [Poeppel is the moderator] New new new! Transformative techniques, game-changing paradigms, groundbreaking schools of thought, and multiple theories for myriad neural circuits. There is no single computational system that can possibly explain brain function at all levels of analysis (gasp! not even the Free Energy Prinicple).3

A Q&A or panel discussion would be nice... (although not on the schedule)


This Special Symposium will be preceded by the ever-exciting Data Blitz (a series of 5 minute talks) and followed by a Keynote Address by the Godfather of Cognitive Neuroscience:

Michael Gazzaniga

The Consciousness Instinct

How do neurons turn into minds? How does physical “stuff”—atoms, molecules, chemicals, and cells—create the vivid and various alive worlds inside our heads? This problem has gnawed at us for millennia. In the last century there have been massive breakthroughs that have rewritten the science of the brain, and yet the puzzles faced by the ancient Greeks are still present. In this lecture I review the the history of human thinking about the mind/brain problem, giving a big-picture view of what science has revealed. Understanding how consciousness could emanate from a confederation of independent brain modules working together will help define the future of brain science and artificial intelligence, and close the gap between brain and mind.


Plus there is a jam packed schedule of posters, talks, and prestigious award recipients/presenters on Sunday through Tuesday. Another highlight:

Symposium 3 The Next 25 Years of Cognitive Neuroscience: Opportunities and Challenges (Brad Postle, Chair)4


I belong to the school of slow blogging, so I probably won't have immediate recaps. Follow #CNS2018 and enjoy the conference!



Footnotes

1 The passenger next to me was watching the Big Bang Theory, so yay for repetition priming.

2 At multiple levels of analysis, e.g. from molecular processes to motor output and all in between. Not daunting or anything. Perhaps not even possible...

3 Although Poster A87 suggests otherwise. {I think}

4 Unfortunately, this conflicts with Symposium 1 Memory Modulation via Direct Brain Stimulation in Humans which I really want to attend as well.

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Sunday, March 18, 2018

Universal Linguistic Decoders are Everywhere

Pereira et al. (2018) - click image to enlarge


No, they're not. They're really not. They're “everywhere” to me, because I've been listening to Black Celebration. How did I go from “death is everywhere” to “universal linguistic decoders are everywhere”? I don't imagine this particular semantic leap has occurred to anyone before. Actually, the association travelled in the opposite direction, because the original title of this piece was Decoders Are Everywhere.1 {I was listening to the record weeks ago, the silly title of the post reminded me of this, and the semantic association was remote.}

This is linguistic meaning in all its idiosyncratic glory, a space for infinite semantic vectors that are unexpected and novel. My rambling is also an excuse to not start out by saying, oh my god, what were you thinking with a title like, Toward a universal decoder of linguistic meaning from brain activation (Pereira et al., 2018). Does the word “toward” absolve you from what such a sage, all-knowing clustering algorithm would actually entail? And of course, “universal” implies applicability to every human language, not just English. How about, Toward a better clustering algorithm (using GloVe vectors) for inferring meaning from the distribution of voxels, as determined by an n=16 database of brain activation elicited by reading English sentences?

But it's unfair (and inaccurate) to suggest that the linguistic decoder can decipher a meandering train of thought when given a specific neural activity pattern. Therefore, I do not want to take anything away from what Pereira et al. (2018) have achieved in this paper. They say:
  • “Our work goes substantially beyond prior work in three key ways. First, we develop a novel sampling procedure for selecting the training stimuli so as to cover the entire semantic space. This comprehensive sampling of possible meanings in training the decoder maximizes generalizability to potentially any new meaning.”
  •  
  • “Second, we show that although our decoder is trained on a limited set of individual word meanings, it can robustly decode meanings of sentences represented as a simple average of the meanings of the content words. ... To our knowledge, this is the first demonstration of generalization from single-word meanings to meanings of sentences.”
  •  
  • “Third, we test our decoder on two independent imaging datasets, in line with current emphasis in the field on robust and replicable science. The materials (constructed fully independently of each other and of the materials used in the training experiment) consist of sentences about a wide variety of topics—including abstract ones—that go well beyond those encountered in training.”

Unfortunately, it would take me days to adequately pore over the methods, and even then my understanding would be only cursory. The heavy lifting would need to be done by experts in linguistics, unsupervised learning, and neural decoding models. But until then...


Death is everywhere
There are flies on the windscreen
 For a start
 Reminding us
 We could be torn apart
Tonight

---Depeche Mode, Fly on the Windscreen


Footnote

1 Well, they are super popular right now.


Reference

Pereira F, Lou B, Pritchett B, Ritter S, Gershman SJ, Kanwisher N, Botvinick M, Fedorenko E. (2018). Toward a universal decoder of linguistic meaning from brain activation. Nat Commun. 9(1):963.





Come here
Kiss me
Now
Come here
Kiss me
Now

---ibid


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