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5 Relation of Visual Perception to Cognition in Parkinson Disease

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Part V



Computational Models

and Integrative Perspectives



Chapter 18



Cognitive and Stimulus–Response Habit

Functions of the Neo- (Dorsal) Striatum

Bryan D. Devan, Nufar Chaban, Jessica Piscopello, Scott H. Deibel,

and Robert J. McDonald



18.1



Introduction: A Historical Perspective



In 1979, the book “The Neostriatum” (Divac and Öberg 1979b), sponsored by the

European Brain and Behavior Society, reported on the proceedings of a workshop

in which researchers of the time representing different specializations presented

their latest findings on this particular part of the brain that has remained enigmatic

even to this day. The Editors of the book, Ivan Divac and Gunilla Öberg, decided to

focus the Vejle meeting in Denmark on the “basic experimental work” to complement two preceding meeting-based volumes (Cools et al. 1977; Yahr and Association

for Research in Nervous and Mental Disease 1976) and deemphasize the topics of

clinical and pharmacological research that was already prominently covered in the

past decade. The goal seemed to be to integrate concepts like “cognitive functions”

and call out proposals of the past to solve the functional puzzle(s) of the neostriatum

within a broad context, with a rich description of the history involved (e.g., Divac

and Öberg 1979a, pp. 215–230) and the divisiveness that had preceded decades

prior to this meeting. Almost 15 years later, when we (RM and BD) were both

beginning our work on multiple memory systems at McGill University, this work

from the late 1970s caught our attention and provided inspiration on a different

perspective that helped us understand some unexpected experimental findings,

given our then present theoretical perspective on “the neostriatum” (or dorsal striatum, a.k.a. cortico-striatal circuits) as a stimulus–response associative system or

B.D. Devan, Ph.D. (*) • N. Chaban • J. Piscopello

Laboratory of Comparative Neuropsychology, Psychology Department, Towson University,

8000 York Rd., Towson, MD 21252, USA

e-mail: bdevan@towson.edu

S.H. Deibel • R.J. McDonald, Ph.D. (*)

Department of Neuroscience, Canadian Center for Behavioral Neuroscience, University of

Lethbridge, 4401 University Drive, Lethbridge, AB, Canada, TIK 3M4

e-mail: r.mcdonald@uleth.ca

© Springer International Publishing Switzerland 2016

J.-J. Soghomonian (ed.), The Basal Ganglia, Innovations in Cognitive

Neuroscience, DOI 10.1007/978-3-319-42743-0_18



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“habit structure” in the mammalian brain (Hirsh 1974; Mishkin et al. 1984; Mishkin

and Petri 1984; Petri and Mishkin 1994). Our view of the dorsal striatum was based

on some very solid and exciting experimental groundwork (McDonald and White

1993; Packard et al. 1989; White et al. 2013), which has since garnered such praise

and recognition to warrant reprint of the original article in the journal Behavioral

Neuroscience (McDonald and White 2013) and is among the most cited findings in

the field, the so-called “double” and “triple” dissociation experiments in rats using

different radial maze tasks (McDonald and White 1993; Packard et al. 1989).

However, some of the work using variations of the water maze task (McDonald and

White 1994) did not seem to fit the model (Devan et al. 1996) and we sought out

other research to explain our findings, including the contents of “The Neostriatum”

as a complement to another influential source, O’Keefe and Nadel’s “The

Hippocampus as a Cognitive Map” published in 1978 (available online in openaccess format at cognitivemap.net).

Part of the answer to our problem was obvious when we compared the placement

of lesions within the striatum. Lesions of the dorsomedial striatum (DMS) seemed

to produce thigmotaxis in the water maze (Devan et al. 1996, 1999), whereas that

was not the case with lesions of the dorsolateral striatum (DLS) which did produce

effects consistent with a simple stimulus–response (S-R) or habit memory system

and parallel to the cognitive-map or “place” functional impairments described for

the effects of hippocampal lesions (McDonald and White 1994). Additional work

confirmed the functional differences between DMS and DLS lesions using variations of McDonald and White’s (1994) competitive cue-place version of the water

maze (Devan 1997; Devan et al. 1999; Devan and White 1999), further suggesting

that, under certain conditions, the DMS may cooperate with the cognitive-based

hippocampal system, while the DLS remained independent, parallel, and even competitive with the hippocampus (McDonald and White 2013). In one experiment, we

even determined the interdependence of connectivity between DMS and hippocampus by showing that crossed-unilateral lesions had the same or similar effects to

bilateral lesions of either structure alone (Devan and White 1999), very powerful

evidence that connections between the structures constitute a functional circuit.

The water maze findings above combined with a non-unitary view of striatal

function related to subregional lesion findings led us to a theoretical proposal based

on associative learning theories with an expanded review of the literature, combined

with new empirical findings related to the above groundbreaking radial maze work

(Devan et al. 2011). For example, we report that DMS lesions facilitate radial maze

cued win–stay behavior (Devan et al. 2011; Devan and White 1997), while previous

studies show that larger lesions of the DLS clearly impair performance on the task

(Devan et al. 2011; McDonald and White 2013; White et al. 2013). Our review of

the literature in 2011 indicated that the associative learning function of the DLS

was a form of simple S–R habit formation, whereas the DMS may contribute to a

higher-order form of (S–S) –R function we referred to as “cognitive control” integrating the allo- and meso-cortical input to DMS with the reinforcement function of

dopamine input to the dorsal striatum that could be combined with relational stimulus information directly conveyed to this region (e.g., López-Figueroa et al. 1995;

McGeorge and Faull 1989).



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Even as far back as Lashley’s 1941 studies of the topographical projection to the

striatum, visual inputs seemed to be restricted to the posterior parts of the structure

(as cited in Iversen 1979). However, more recent studies show visual input projecting to longitudinal territories within the DMS of the rat (López-Figueroa et al.

1995), with pre-terminal fibers forming “fluffs” that correspond with weak calbindin staining and yet belong to the matrix compartment. Many association cortical

areas project to longitudinal territories with restricted medial–lateral domains in the

monkey with some interdigitation of terminal regions consistent with neurochemical compartmentalization (e.g., Selemon and Goldman-Rakic 1985).

Given the lack of direct visual input to the DLS, in 2011, we hypothesized that

impairments of simple visual S–R tasks may rely on the reinforcement function of

striatal dopamine evoked by unconscious visual sensory information via a phylogenetically older series of connections from the superior colliculus to the substantia

nigra and striatum (via the thalamus) in both primates and rats (Coizet et al. 2003,

2007; May et al. 2009), providing a slow incremental strengthening of S–R associations over time, consistent with the longer time intervals to improved accuracy of

discriminative behavior to develop for win-stay and other habit tasks. Redgrave

et al. (2010) point out that the superior colliculus provides afferent signals to the

other input nuclei of the basal ganglia, the dopaminergic neurons in substantia

nigra, and to the subthalamic nucleus. Their recent electrophysiological data show

that the afferent signals originating in the superior colliculus carry important information concerning the onset of biologically significant events to each of the basal

ganglia input nuclei that may be crucial for the proposed functions of selection and

reinforcement learning within the striatum.

Divac and Öberg (1979a) pointed out that many studies and theories tend to

ignore or fail to appreciate the anatomical heterogeneity within the neostriatum, and

we further suggested that the inconsistency in nomenclature over the years has contributed to the confusion, hence our proposal for distinguishing DLS and DMS subregions of the dorsal striatum after a fairly represented review of the neuroanatomical

literature on the subject, integrating the re-defined anatomical/connectivity nomenclature to neurobehavioral findings—including lesion, electrophysiological, some

pharmacological studies, and consideration of hippocampal and prefrontal relations

to dorsal striatum along with a lengthy discussion of various conceptual frameworks,

pointing out the strengths and weaknesses of different associative learning models

and experimental protocols (e.g., stimulus devaluation studies and R–O and S–O

learning processes), the details of which may be re-visited in our previous review.

Divac and Öberg (1979a) also claimed that “inhibitory” and “motor” theories of

neostriatal function were too general and could be applied to many areas of the

brain, thus rendering such “theories” less meaningful and useful for modern functional conceptions. As Iversen (1979) pointed out in her chapter, even the early

anatomical studies in rats, rabbit, cat, and monkey showed that the striatum receives

a highly organized projection apparently from all areas of the neocortex, leading to

the logical conclusion that prior exclusive emphasis on motor functions missed the

exciting and important alternative of cognitive functions, citing an influential

statement by Lashley (1950; S.E.B. Symposium IV, pp. 454–482) that the conclusive



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evidence in mammals showed that the basal ganglia are not an essential link in the

patterning of learned activities (as cited in Iversen 1979, p. 195), a statement that is

directly opposed to the current focus on learning functions of the striatum and for

which much evidence has accumulated over the years (e.g., White 2009). In a tribute to Ivan Divac, Dunnett (1999) describes a classic experiment in which lesions of

three different subregions of prefrontal cortex and the corresponding input subregion within the head of the caudate nucleus produce similar behavioral impairments

on different learning tasks, demonstrating that cortico-striatal circuits mediate different learning functions, providing an early triple dissociation centered on subregions within the neostriatum.

Our historical perspective is offered to provide a strong background to integrate important unacknowledged advances in thought that have laid the groundwork for our current assessment of recent work. With our modern emphasis on

new scientific findings using the latest state-of-the-art technique, whether tried

and true or an artefactual data generation (e.g., Boubela et al. 2015) that becomes

apparent after it’s already “out there,” the past is vulnerable, even likely to be lost,

as the more recent work replaces what has come before. Arguably, the most important contribution of our previous review of the literature is the attention we gave

to the historical context that came before with a chaotic, incoherent variety of

theoretical proposals that, in the end (and beginning), tend to really have a level

of organization that is amazingly ordered, structured, and almost entirely consistent with the emerging neuroanatomical data. Although theories are often sold as

novel, different, and a significant advancement in science, truth be told, a step

back to see the broader context can show a clearer and more coherent picture to

increase our level of understanding. Consequently, we identified several theories

in a nonexhaustive, but representative, table that showed two categories or themes

that emerged from a survey of the theoretical and scientific review literature of the

early work in the field. Using the general terminology common to the debate, we

categorized theories as emphasizing motor or cognitive functions, though many

were beginning to include elements of both, and some even distinguished regional

variations in neuroanatomy.

The late 70s were an amazingly productive time where researchers considered

all relevant ideas of their peers and acknowledged research to build upon the established literature and knowledge (e.g., Divac & Öberg, 1979a, b). We wish to continue this traditions by providing a critical analysis and integration of findings from

more recent work in the field. In that tradition, we continue with the following new

integration since 2011. Theory building could proceed like selling snake oil—

what’s unique that you must have to end the dilemma—or it could actually build,

acknowledging the value and merit of “other” work, how it relates and also differs

from your own, and attempt to tie it all together in a narrative that makes sense out

of the seemingly disparate and incoherent arguments we have no doubt encountered

in the past and that are often not even internally consistent.

The main point we try to make in the first section of this chapter is that there

are similarities and differences between species in basal ganglia anatomy (focusing on circuit connectivity and neurochemical compartmentalization). Despite the

differences, however, a general tripartite model enables functional specialization



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between associative, limbic, and motor loops for parallel processing, while also

allowing important interactions between subregions at the local cortico-striatal

patch/matrix level (inter-digitation and cross boundary interactions by interneurons), and as recent research shows, through interactions between circuits via

diverse mechanisms involving modulatory midbrain structures, thalamic relays,

and cortical integration (open-circuit interactions) coordinating behavior to both

build higher-order habits and to take such secondary automatisms off-line when

cognitive control is required to deal with new situations in a flexible manner. The

subsystems interact in such a way to build future habits when consistent reinforcement contingencies are stable over time to allow abstract relational (cognitive/spatial/configural) information to manifest as complex habits. In turn,

prefrontal working memory function and other high-level cognitive resources

engage new “hypothesis testing,” or “vicarious trial and error,” supporting dramatic shifts in performance that may result from new insight or the slow incremental buildup of cognitive–habit strength all along, forming a continuous

interplay in problem-solving and associative learning. In the second half of the

chapter, our goal is to emphasize several major directions the field is progressing

toward, provide a critical evaluation that will hopefully ultimately lead to an integration of meritorious work to further clarify cortico-striatal functions, parallel

processing and integration in order to further elucidate its role(s) in various disorders and to better understand at some level of coherence, states of function and

often dysfunction, possibly leading to productive avenues for future research on

neurodegenerative diseases and neuropsychological dysfunctions. Basic research

has often proven to be an essential element in the step toward therapeutic intervention and drug discovery. The areas we will explore include: (1) an assessment

of single-unit electrophysiological research in freely behaving rodents from the

past and present and (2) an evaluation of some Bayesian computational approaches

to understanding sensorimotor learning and the role of striatal regions.

As a Forerunner to Bayesian statistical approaches was David Hume’s skepticism about cause and effect, which led him to attack some of Christianity’s fundamental narratives (Mcgrayne 2011). Hume believed that we cannot be absolutely

certain about anything based on cause and effect, traditional beliefs, testimony,

habitual relationships, etc.; we can only rely on what we learn from experience. Our

model (Devan et al. 2011) was built on specific scientific findings leading individuals to posit theories of striatal function (initial beliefs), which we have in a sense

used in a Bayesian inverse probability problem to understand. Based on Bayes’

original thought experiment idea of throwing balls on an even table with his back

turned so as not to know the final resting place/outcome of any ball, only that it

rested to the left or right of the original, we essentially ask—given the sampling of

empirically based theoretical proposals “thrown on the table” so to speak (i.e., the

Likelihood for the probability of other hypotheses) following the Prior for the probability of the original belief dating back to Thomas Willis’ 1664 observation that the

corpus striatum receive input from all sensory modalities, consistent with Aristotle’s

sensorium commune, how likely is it that striatal function is based on habit formation or a cognitive control function (i.e., Posterior for the probability of the newly

revised belief)?



418



B.D. Devan et al.



What we have essentially argued is that the original hypothesis or guess (Prior)

possessing elements of each argument landed nearly smack in the middle of the

table, with our or newly revised belief (Posterior), supporting an approximately

equal number of subsequent instances of recent objective data (Likelihood) landing

to the left and to the right of the Prior. In other words, both conclusions are correct

and the myth that there must be a unitary original location or conclusion is, though

conceptually appealing and parsimonious, is itself overly simplistic and possibly in

error. Our conclusion is more in line with the superposition or ‘spooky behavior’ of

elections and photons occupying multiple locations at once in quantum physics. All

too many times have we been humbled in neuroscience when we think we have

established a single new rule or principle of neural function and then soon thereafter

realize the exceptions (e.g, action potentials can travel bi-directionally on dendrites). Mishkin and Petri (1984) have pronounced an end to the great debate among

learning theorists, neuropsychology declares both the winners, as evidence shows

that the mammalian brain contains multiple memory systems. The starting point of

a process for Bayesian modeling that doesn’t end, but rather builds on what has

come before, effect before cause (see also, Hirsh 1974; Mishkin et al. 1984; Petri

and Mishkin 1994).

To establish a beginning point, A PubMed search including all search fields for

“striatum AND theory” and “basal ganglia AND theory” produced a combined

number of 667 papers with duplicates removed and without any year restriction.

Earlier, we highlighted 25 early proposals of the function(s) of basal ganglia in

2011, based on a systematic yet informal sampling of papers that we encountered

frequently in the literature. The goal was not to present a comprehensive list, which

by the standards outlined above would be quite large. Our point was to use the sampling of early studies to detect trends in categorical affiliation with motor or nonmotor cognitive forms of functional proposals. Based on our assessment, many theories

had elements of both but differed in the emphasis placed on one of the two alternatives. Divac and Öberg (1979a) warned that although the neostriatum may appear

homogeneous with more-or-less explicit assumptions of functional homogeneity

unfortunately dominating main-stream conceptions at the time, we concluded that

the homogeneous/unitary trend along with some attempts to integrate, still with a

clear emphasis on one component or the other, continued up to the time of our

review. The present trend toward expansion of theoretical ideas on the striatum,

given the results of the PubMed search mentioned above, illustrates an exponential

effort to understand the functions of the striatum, the lack of any unifying theory

seems less tenable and even further beyond reach, though many theorists will tell

you that they embrace a particular perspective until “sufficient” evidence to the

contrary demands a new functional formulation and finally that the approaches used

to address the theoretical issues have increased in a field that depends heavily on

technological advances to generate new approaches or empirical data to attack the

problems on several fronts, even if such techniques are blatantly flawed or provide

only weak evidence at best that often is over-interpreted.



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