Schizophrenia Computer Model DISCERN Hoffman Yale 2011

May 06, 2011 09:25 AM   free and online;  from YALE;  also in my Neuro files.

pub in Biol Psyciatry  15 May 2011

first author is Ralph Hoffman, YALE.  pdf in my files.

Certain language behaviors are characteristic of schizophre-

nia. Spoken discourse often fails to express a cohesive mes-

sage (1–4). Many patients express ﬁxed delusions as spuri-

ous narrative schema repeated over time intervals ranging from

weeks to years (5,6).

Mechanisms causing these behaviors remain uncertain. Lan-

guage disorganization has been associated with disrupted working

memory, semantic processing, attention, and linguistic context (7–

21), while delusions have been associated with aberrant emotion-

based reasoning and associative learning, anomalous perceptions,

and jumping to conclusions (22–25). Both syndromes have been

associated with disturbed executive functioning (22,26,27), theory

of mind (22,28,29), and dopamine neuromodulation (30,31) and

elevated hippocampal/parahippocampal activation (32–34). In this

situation, connectionist models employing artiﬁcial neural net-

works can be used to compare the likelihood of alternativemecha-

nisms and tie together explanations of seemingly disparate symp-

toms and experimental ﬁndings.

DISCUSSION  p 2002

Discussion

Whereas all eight illness mechanisms were equivalent in matching

the healthy control narrative breakdown profile, hyperlearning

was significantly better than the others in matching the narrative

breakdown profile of patients. The differential advantage of hyperlearning

in matching patient story-recall data suggests that exaggerated

prediction-error signaling during memory consolidation

captures pathophysiology underlying schizophrenia specifically

rather than nonspecific story-recall distortions demonstrated by

human subjects overall.

A majority of three-parameter best-fit hyperlearning simulations

also recurrently confused specific agents in personal stories

(including the self-representation) with specific agents in crime

stories (and vice versa) in a highly nonrandom fashion. Noteworthy

was the high frequency of agent-slotting exchanges between the

hospital boss, Joe, and the Mafia boss, Vito, and parallel confusions

between the “I” self-reference and underling Mafia members,

suggesting generalization of boss/underling relationships. Insofar

as story scripts provide templates for assigning intentions to agents

(68), a consequence of recurrent agent-slotting confusions could

be assignment of intentions and roles to autobiographical characters

(possibly including the self) that borrow from impersonal stories

derived from culture or the media. Confusion between agent

representations in autobiographical stories and those in culturally

determined narratives could account for the bizarreness of fixed,

self-referential delusions, e.g., a patient insisting that her father-inlaw

is Saddam Hussein or that she herself is the Virgin Mary. This

Fixed delusion  (p 2003, bot of 1st column) are storyt memories

contaminated by misappropriated agents.

abnormalities

in schizophrenia during associative learning (25,69,70) to learning

narrative sequences stored as episodic memories. The model is

consistent with a mechanistic role of excessive dopaminergic release

in schizophrenia (31,71,72) insofar as dopamine release appears

to enhance memory consolidation and prediction-error signaling

(61,73,74). In humans, hyperlearning would likely require

greater activation in hippocampal structures central to consolidating

episodic memories (75–77). This formulation accounts for elevated

baseline activation in hippocampal regions demonstrated in

patients with schizophrenia (33,34), which appears to be reduced

by antipsychotic medication (78); these medications may therefore

achieve antipsychotic effects by curtailing hyperlearning, possibly

by dopamine antagonistic effects (79).

Schizophrenia Computer Model DISCERN Hoffman Yale 2011

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