36.985, Books: Speaking Brains: Joseph Galasso (2025)
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LINGUIST List: Vol-36-985. Fri Mar 21 2025. ISSN: 1069 - 4875.
Subject: 36.985, Books: Speaking Brains: Joseph Galasso (2025)
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Date: 20-Mar-2025
From: Ulrich Lueders [contact at lincom.eu]
Subject: Speaking Brains: Joseph Galasso (2025)
Title: Speaking Brains
Subtitle: Collective Papers on AI, Neuro-circuitry and Basal Ganglia
Grammar
Series Title: LINCOM Studies in Neurolinguistics 04
Publication Year: 2025
Publisher: Lincom GmbH
https://lincom-shop.eu/
Book URL:
https://lincom-shop.eu/epages/57709feb-b889-4707-b2ce-c666fc88085d.sf/en_GB/?ObjectPath=/Shops/57709feb-b889-4707-b2ce-c666fc88085d/Products/%22ISBN%209783969392065%22
Author(s): Joseph Galasso
Abstract:
ISBN 9783969392065 (paperback), 17x24 cm, 96pp., EUR 69.80.
The most compelling evidence to date for involvement of the Basal
Ganglia (BG) (Basal Ganglia Grammar) in natural language comes to us
from theoretical movement operations (nested dependency, distant
binding and trace-theory). This implication of BG overlaps with
well-established evidence showing Broca’s involvement with movement.
Dual pathways are a marked characteristic of BG insofar that in
cascading down-stream neural networks, both direct as well as indirect
paths affect admixed neuronal populations from multiple cortical
areas. A tentative proposal may suggest that any notion of duality at
the subcortical level may have the ability to simulate what we know of
local vs distant binding dependencies as found in Dual Mechanism Model
accounts of natural language. A theoretical (meta)-synthesis which
seeks to connect what we know of Natural Language (NL) with current
trends in AI/Transformers may offer us a potential merging of what has
up until now been two quite disparate underlying systems. If we assume
that NL systems mirror what we find in Parallel Distributed Processing
(PDP) across neural networks—and via extension be applicable to any
putative AI/Transformer-to-NL corollary—then, by definition, some
component of the PDP would necessarily entail a capacity-state which
corresponds to concepts, symbols and categorial rules—i.e., real
recursive-based prerequisites for natural language which up until now
have been sidelined in the implementation of AI modeling.
Linguistic Field(s): Neurolinguistics
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