| Koch;
Large-Scale Neuronal Theories of the Brain |
|
|
| Chapter |
Page |
|
Topic |
|
|
| Domasio;
Convergence Zone |
66 |
|
Conjoining
of nonverbal and verbal activated representations
pertaining to concrete entities depends on a mediator
mechanism in left anterior temporal cortices.
The mechanism promotes the reconstruction of a
word form given the concept, or, conversely, the reconstruction
of the concept of an object given the word form. |
|
|
| Domasio; Convergence Zone |
67 |
|
Mediational mechanism for words and concepts do not contain records for either words or concepts
themselves but rather records of the probable combination between them. |
|
1 |
| Domasio; Convergence Zone |
68 |
|
Access to concrete knowledge of higher hierarchical status requires structures in anterior temporal cortices,
whereas access to concrete knowledge of lower complexity only requires posterior occipital cortices. |
|
1 |
| Domasio; Convergence Zone |
68 |
|
Because of cerebral
hemisphere dominance effects, certain types and
levels of knowledge may require an anterior or
intermediate cortex of one
hemisphere only. |
|
0 |
| Domasio; Convergence Zone |
68 |
|
Knowledge
that can be accessed from the brain's neural network is not stored as an "image".
Rather, the neural assemblies with their hierarchical
convergence zones can provide network activity that may reenact the original explicit representation. |
|
0 |
| Domasio;
Convergence Zone |
68 |
|
Cells in high-order cortices forming the hierarchy of convergence zones are
critical for the neural process of memory reenactment, but they are
neither the "sole basis for" nor the "explicit site of"
that neural process. There is no single basis or
site for such a process. Each memory reenactment can
utilize slightly different neural assemblies. |
|
0 |
| Domasio; Convergence Zone |
70 |
|
Top steps in the hierarchy are the most distant convergence
points from which divergent
retroactivation can be triggered. |
|
2 |
| Domasio;
Convergence Zone |
70 |
|
There is a ceaseless
production of new
activity states, in early
sensory cortices and in motor
cortices, across time. It is these successive neural states, one after
the other, that can be said to constitute "regresses" for the
previous state. Neural assemblies are activated
(refreshed) in a pulse-like manner by reentrant signals circulating in the network hierarchy.
It is the perpetually recursive property of corticocortical systems that permits this special form of
regress.
[recursion] [Bayesian
inference] [Fuster's perception-action cycle] |
|
0 |
| Domasio; Convergence Zone |
71 |
|
The reconstruction of pertinent property "representations" is
accomplished in many separate cortical regions by means of long-range
corticocortical feedback projections that mediate relatively synchronous excitatory activation. |
|
1 |
| Domasio; Convergence Zone |
71 |
|
In the large scale reconstruction from higher-order cortices such as those
in anterior temporal lobe, the time scale of the
synchronization would be in the order of several hundred msec, and even beyond 1000 msec, the scale
required for meaningful, conscious cognition. |
|
0 |
| Domasio; Convergence Zone |
71 |
|
At more local
levels, for instance, in posterior temporal cortices, the
scale would be smaller, in the order of tens of
milliseconds. The return
projections necessary for the reconstruction are aimed toward layers I and V of the cortex. |
|
0 |
| Domasio; Convergence Zone |
71 |
|
A convergence
zone is an ensemble of neurons within which many feedforward/ feedback loops make contact. |
|
0 |
| Domasio; Convergence Zone |
71 |
|
A convergence
zone is located within a convergence region. |
|
0 |
| Domasio; Convergence Zone |
71 |
|
There are in the order of thousands of convergence zones, which are all microscopic neuron
ensembles, located within the macroscopic convergence regions that have been cytoarchitectonically
defined and that number about one hundred. |
|
0 |
| Domasio; Convergence Zone |
71 |
|
Both convergence
regions and convergence
zones come into existence under genetic control. |
|
0 |
| Domasio; Convergence Zone |
71 |
|
Epigenetic control, as the organism interacts with
the environment, may alter
convergence regions and massively alter convergence zones
through synaptic strengthening. |
|
0 |
| Domasio; Convergence Zone |
72 |
|
A convergence
zone is a means of
establishing, through synaptic strengthening, preferred feedforward/feedback
loops that use subsets
of neurons within the ensemble. |
|
1 |
| Domasio; Convergence Zone |
72 |
|
A subset of
the neurons in the convergence
zone would "learn"
to activate a large
number of spatially
distributed neural ensembles, in temporal proximity, by means of feedback projections. |
|
0 |
| Domasio;
Convergence Zone |
72 |
|
A convergence
zone develops under
the influence of (1) temporally
close activity in multiple feedforward and feedback lines that are simultaneously active when a number of anatomically separate regions are active and are providing the normal
substrate for a given perceptual/thought
process, and (2) modulatory
action from feedback
and feedforward projections from ipsilateral and contralateral cortices, and subcortical nuclei. |
|
0 |
| Domasio; Convergence Zone |
72 |
|
The development
of a convergence zone
also depends on local interactions among neurons (e.g., from their intrinsic collateral arborizations). |
|
0 |
| Domasio; Convergence Zone |
72 |
|
A convergence
zone would be the result of convergence of feed-forward inputs, but its feedback projections operate by diverging toward the origin of feedforward projections. |
|
0 |
| Domasio; Convergence Zone |
72 |
|
When we refer to neurons in a convergence zone we
refer to the synaptic pools made up of contacts among those
neurons. |
|
0 |
| Domasio; Convergence Zone |
73 |
|
Knowledge retrieval would be based on relatively simultaneous, attended activity
in many early cortical regions, intended over several recursions. |
|
1 |
| Domasio; Convergence Zone |
73 |
|
Separate activities in early
cortices would be the basis for reconstructed representations. |
|
0 |
| Koch and
Crick; Neuronal Basis |
95 |
|
To be aware of an object or an event the brain has to construct an explicit, multilevel, symbolic interpretation of a feature of the visual scene. By explicit we mean that a coherent neural assembly must be firing
above background at
that particular time in response to the feature they symbolize. |
|
22 |
| Koch and
Crick; Neuronal Basis |
95 |
|
The term multilevel means, in psychological terms, different levels such as those that correspond, for example, to lines, eyes, or faces. In neurological
terms it means, loosely, the different levels in the visual hierarchy. |
|
0 |
| Koch and
Crick; Neuronal Basis |
95 |
|
The term 'symbolic'
as applied to a neural
assembly means that assembly's
firing is strongly
correlated with some 'feature' of the visual world and thus symbolizes it. The meaning of such a symbol depends not only on the neuron's receptive field but also on what other neural assemblies the neuron projects to. |
|
0 |
| Koch and
Crick; Neuronal Basis |
95 |
|
Awareness
results from the firing
of a coordinated
subset of thalamocortical neurons that fire in some special manner for a certain length of time, probably
for at least 100-200
msec.
This firing needs to activate some type of short-term
memory by either strengthening
certain synapses or maintaining an elevated firing rate or both. |
|
0 |
| Koch and
Crick; Neuronal Basis |
96 |
|
Movement is
extracted early in the visual system as a primitive. |
|
1 |
| Koch and
Crick; Neuronal Basis |
97 |
|
Blindsight |
|
1 |
| Koch and
Crick; Neuronal Basis |
97 |
|
Active neurons in the cortical
system that are apart from awareness activity at the moment can still lead to
behavioral changes but without awareness. These neurons are responsible for the large class of
phenomena that bypass awareness in normal subjects, such as automatic processes, priming, subliminal perception, learning
without awareness, and others. |
|
0 |
| Koch and
Crick; Neuronal Basis |
97 |
|
We suspect that the majority of neurons in the cortical
system at any given time
are not directly associated with awareness! |
|
0 |
| Koch and
Crick; Neuronal Basis |
98 |
|
Rate coding -
the simplest encoding uses mean firing frequency. |
|
1 |
| Koch and
Crick; Neuronal Basis |
99 |
|
Hypothesized that all neurons
corresponding to various aspects of the object the observer is attention to
fire in an oscillatory and semisynchronous manner, binding them together |
|
1 |
| Koch and
Crick; Neuronal Basis |
101 |
|
Original hypothesis was that the
phase-locked firing of a set of neurons at 40 Hz was the neural correlate of
visual awareness. |
|
2 |
| Koch and
Crick; Neuronal Basis |
101 |
|
Lower-layer hypothesis states
that the neural correlates of visual awareness occur mainly in the lower
layers 5 and 6 of the cortex. The input layer as well as neurons in the upper
layers 2 and 3 are assumed to be mainly concerned with unconscious processing. |
|
0 |
| Koch and
Crick; Neuronal Basis |
101 |
|
Cognitive scientists have
suggested that the content of consciousness consists of the results of neural
computation while the
interim results associated with the computations
leading up to these results are themselves largely
unconscious. |
|
0 |
| Koch and
Crick; Neuronal Basis |
102 |
|
The corticospinal
pyramidal tract, with
one million axons, the
largest descending fiber tract from the human
brain, originates in layer
5 of primary motor, supplementary motor,
and premotor cortical areas
and projects onto interneurons and motorneurons in the spinal cord. |
|
1 |
| Koch and
Crick; Neuronal Basis |
102 |
|
The massive projection system linking virtually the entire
neocortex with the striatum originates in layer 5. |
|
0 |
| Koch and
Crick; Neuronal Basis |
102 |
|
What the cortex
sends elsewhere in the brain are likely to be the
results of its computations. |
|
0 |
| Koch and
Crick; Neuronal Basis |
104 |
|
Two thirds
of neurons often fire in bursts of 2-4 spikes within 2-6 msec and show a small peak in the 25-50 Hz band of the power spectrum that is related to the propensity
of spikes to fire in
bursts. The statistical
properties can be fitted by Poisson-distributed bursts with a burst-dependent refractory
period. |
|
2 |
| Koch and
Crick; Neuronal Basis |
104 |
|
The
remaining third of their cells have an autocorrelation function and an interspike interval distribution
compatible with the notion that spikes are
Poisson distributed with a refractory period. |
|
0 |
| Koch and
Crick; Neuronal Basis |
106 |
|
Pyramidal cells in both layer 5 ands layer 6 project to the various thalamic
nuclei, including the lateral geniculate nucleus
(LGN), as well as the inferior, lateral, and medial pulvinar nuclei. |
|
2 |
| Koch and
Crick; Neuronal Basis |
106 |
|
In primate area V1, cells in
layer 5 as well as the deep part of layer 6 project to the pulvinar, while
higher cortical areas project from the deep layers into the different
pulvinar nuclei. |
|
0 |
| Koch and
Crick; Neuronal Basis |
106 |
|
About half of all pyramidal cells in layer 6 project back to the LGN while
others project to the claustrum. This corticogeniculate projection is so massive that at least 10 times more
fibers project down than project from the LGN in V1. |
|
0 |
| Koch and
Crick; Neuronal Basis |
107 |
|
An essential feature of visual processing may turn out to be the back projections to V1 (or conceivably to V1 and/or V2) as these areas are the only
ones with detailed information about precise visual location. |
|
1 |
| Koch and
Crick; Neuronal Basis |
107 |
|
While
inferotemporal regions do
not receive a direct projection from V1, they do send backprojections to V1. |
|
0 |
| Koch and
Crick; Neuronal Basis |
107 |
|
Reentrant projections strongly emphasized by Edelman. |
|
0 |
| Koch and
Crick; Neuronal Basis |
107 |
|
Massive reentrant connections formed by the hippocampal system in the medial temporal lobe. Input
comes mainly from the entorhinal
cortex, and its output
returns there, though to a different cortical
layer. |
|
0 |
| Koch and
Crick; Neuronal Basis |
109 |
|
The brain
constructs an explicit,
multilevel, symbolic interpretation of parts of its environment. [Llinás;
brain operates as a reality emulator.] |
|
2 |
| Koch and
Crick; Neuronal Basis |
109 |
|
The form of awareness associated with focal attention is caused by the firing of a temporally coordinated assembly of
neurons, firing in some special manner for at least 100 or 200 msec. This special form of neuronal activity induces short-term memory. |
|
0 |
| Koch and
Crick; Neuronal Basis |
109 |
|
If neurons
are not part of the transient
subset of activity, they can still influence behavior but do not contribute toward
awareness.
[Edelman's dynamic core] |
|
0 |
| Koch and
Crick; Neuronal Basis |
109 |
|
Underlying every direct perception is a group of neurons strongly firing
and participating in the temporally coordinated neuronal assembly. [Edelman's dynamic
core] |
|
0 |
| Koch and
Crick; Neuronal Basis |
109 |
|
Semisynchronous, neuronal oscillations in the 25-55 Hz band could cause neurons to be coordinated, giving
rise to short-term memory and thus to awareness. [Edelman's dynamic
core] [Baddeley - Working Memory] |
|
0 |
| Koch and
Crick; Neuronal Basis |
109 |
|
The neural
correlate of awareness
occurs mainly in the lower
layers. |
|
0 |
| Koch and
Crick; Neuronal Basis |
109 |
|
The neural
correlate of awareness
is associated with the bursting neurons in layer 5, some of which project outside the
cortical system. |
|
0 |
| Koch and
Crick; Neuronal Basis |
109 |
|
The loop between deep layers in cortex, the different thalamic nuclei, and back to cortex may implement short-term memory. [reentry]
[Edelman's dynamic core]
[Baddeley - Working Memory] |
|
0 |
| Koch and
Crick; Neuronal Basis |
109 |
|
Neurons in
the upper cortical layers, are mainly concerned with unconscious
processing. |
|
0 |
| Koch and
Crick; Neuronal Basis |
109 |
|
Various types of neural connections may be
associated with some forms of visual awareness. Possible examples are: (1) Connections to the hippocampal system and the higher planning levels of the motor system, (2) direct back projections to V1
and possibly V2, and (3) reentrant connections within layer 4 or between cortical areas at the same level in the anatomical hierarchy.
|
|
0 |
| Llinás; Perception as Oneiric-like |
113 |
|
Wakefulness
is a dreamlike state modulated
by specific sensory inputs. |
|
4 |
| Llinás; Perception as Oneiric-like |
113 |
|
Thalamus is
regarded as the functional and morphological gate
to the forebrain. With the exception of the olfactory system,
all sensory messages reach the cerebral
cortex through the thalamus. |
|
0 |
| Llinás; Perception as Oneiric-like |
113 |
|
Connectivity
between the thalamus and the cortex is bidirectional. Layer 6 pyramidal cells project
back to the area of
the thalamus where their specific input arises, and layer 5 cells project to the nonspecific thalamus. |
|
0 |
| Llinás; Perception as Oneiric-like |
113 |
|
The number
of corticothalamic fibers is about one order of magnitude larger than
the number of thalamocortical axons. |
|
0 |
| Llinás; Perception as Oneiric-like |
113 |
|
The number of optic nerve axons projecting to the LGN is much smaller than the number of corticothalamic axons projecting
to the LGN. |
|
0 |
| Llinás; Perception as Oneiric-like |
113 |
|
Sensory input from the thalamus
is necessary for perception; however, the specific
thalamocortical input accounts for a minority of the synaptic contacts in the cortex. |
|
0 |
| Llinás; Perception as Oneiric-like |
114 |
|
Electrophysiological studies
indicate that the intrinsic membrane properties of
neurons allow them to oscillate or resonate at different frequencies.
This intrinsic neuronal support of rhythmic oscillatory activity may play a fundamental role in CNS function. |
|
1 |
| Llinás; Perception as Oneiric-like |
114 |
|
The brain is essentially a closed system capable of self-generated oscillatory activity
that determines the functionality of events specified by the sensory stimuli. |
|
0 |
| Llinás; Perception as Oneiric-like |
114 |
|
Only a minor
part of thalamocortical
connectivity is devoted to the reception and
transfer of sensory input. |
|
0 |
| Llinás; Perception as Oneiric-like |
114 |
|
The number
of cortical fibers projecting to the specific thalamic nuclei is much larger than the number of fibers conveying the sensory information to the thalamus. |
|
0 |
| Llinás; Perception as Oneiric-like |
114 |
|
A large part of the thalamocortical connectivity is organized in what is presently known as reentrant activity (Edelman) or previously
viewed as reverberating
activity. |
|
0 |
| Llinás; Perception as Oneiric-like |
114 |
|
Neurons
with intrinsic oscillatory capabilities in the complex synaptic network allow the brain to generate
dynamic oscillatory states, which can shape the computational events
evoked by sensory stimuli. |
|
0 |
| Llinás; Perception as Oneiric-like |
114 |
|
Functional states such as wakefulness (or REM sleep and other sleep stages)
appear to be particular examples of the multiple variations provided by the self-generated brain activity. |
|
0 |
| Llinás; Perception as Oneiric-like |
115 |
|
The
localization of function in the brain began with
the identification of a cortical speech center by Broca and was followed by the discovery of point-to-point somatotopic maps in
the motor and sensory cortices (Penfield and Rasmussen 1950), and in the thalamus (Mountcastle and Hennemann 1949, 1952). |
|
1 |
| Llinás; Perception as Oneiric-like |
115 |
|
A totally different type of functional geometry (Pellionisz and
Llinas 1982) suggests
the existence of temporal mapping. This has been far more difficult to conceptualize, since its
study requires an understanding of simultaneity
in brain function not
usually considered in neuroscience. |
|
0 |
| Llinás; Perception as Oneiric-like |
115 |
|
Magnetoencephalographic
recordings performed in awake humans revealed the
presence of continuous and coherent 40-Hz oscillations over the entire cortical mantle. |
|
0 |
| Llinás; Perception as Oneiric-like |
115 |
|
Phase comparison of the oscillatory
activity recorded from different
cortical regions revealed the presence of a 12- to 13-msec phase shift between
the rostral and caudal pole of the brain. |
|
0 |
| Llinás; Perception as Oneiric-like |
118 |
|
Magnetoencephalography (MEG) was used in three sets of studies concerning: (1) the
presence of 40 Hz activity during sleep, (2) the possible differences between 40 Hz resetting in different sleep/wakefulness states, (3) the
question of 40 Hz during
REM sleep. |
|
3 |
| Llinás; Perception as Oneiric-like |
118 |
|
In the MEG
studies, spontaneous
magnetic activity was continuously recorded and filtered at 35-45 Hz during wakefulness,
delta sleep, and REM
sleep, using a 37-channel
sensor array. |
|
0 |
| Llinás; Perception as Oneiric-like |
118 |
|
Fourier analysis of the spontaneous, broadly
filtered rhythmicity (1-200
Hz) demonstrated a large peak of
activity at 40-Hz over
much of the cortex. |
|
0 |
| Llinás; Perception as Oneiric-like |
119 |
|
During wakefulness and REM sleep, a very specific 40-Hz
thalamocortical resonance is active and has very
similar global properties. |
|
1 |
| Llinás; Perception as Oneiric-like |
120 |
|
Front-to-back phase shift of the 40-Hz
activity over the head during REM sleep;
well-organized 12-msec phase shift for the 40-Hz
oscillation; |
|
1 |
| Llinás; Perception as Oneiric-like |
120 |
|
Overall speed
of the rostrocaudal scan,
which averaged approximately 12.5 msec, corresponded quite closely to half
a 40-Hz period. This number is the same as that
calculated for a quantum of consciousness in psychophysical studies in the auditory system. |
|
0 |
| Mumford; Neuronal Architectures |
135 |
|
In the cortex, roughly 65% of all cells are pyramidal
cells that send their output
to distant cortical areas, as well as locally via their axon collaterals. |
|
15 |
| Mumford; Neuronal Architectures |
135 |
|
Pattern theory says that tightly coupled cortical
areas seek, via some kind of relaxation functionality, to
arrive at a mutual agreement in which lower areas' specific data form a fit with known, more abstract categorizations stored in
higher areas' memory of prior activity. |
|
0 |
| Mumford; Neuronal Architectures |
135 |
|
Bottom-up assertions of facts have to be included along
with top-down
memories of expected patterns. |
|
0 |
| Mumford; Neuronal Architectures |
136 |
|
Correlated spikes from full spike trains may be more meaningful than responses from individual
neurons. |
|
1 |
| Mumford; Neuronal Architectures |
136 |
|
Set of spikes
may be much less
stochastic,
carrying information transmitted between areas, and correlated
much more precisely and predictably with identifiable
aspects of an input. |
|
0 |
| Posner; Constructing Neuronal Theories |
188 |
|
Anterior cingulate gyrus has strong connections with a variety of other neural
areas and plays a critical
role in attention and what is meant by consciousness, and relates both to awareness and to voluntary control. |
|
52 |
| Posner; Constructing Neuronal Theories |
189 |
|
Subjective experience is related to activation of the anterior
cingulate attention
system. |
|
1 |
| Posner; Constructing Neuronal Theories |
189 |
|
Degree of activation of the anterior cortex attention
system increases with the number of targets presented in a
semantic monitoring task and decreases with the
amount of practice in the task. |
|
0 |
| Posner; Constructing Neuronal Theories |
189 |
|
Anterior cortex attention system is active during tasks requiring the detection of visual stimuli, when
the targets involve color, form, motion, or words semantics. |
|
0 |
| Posner; Constructing Neuronal Theories |
189 |
|
Anterior attention system is activated when listening passively to words, but not when watching these words. |
|
0 |
| Posner; Constructing Neuronal Theories |
189 |
|
Intrusive nature of auditory
words to consciousness when they are presented in a quiet background. Auditory
words seem to capture awareness. Reading does not
have this intrusive character. |
|
0 |
| Posner; Constructing Neuronal Theories |
190 |
|
Anterior cortex attention system is more active during conflict blocks than during non-conflict
blocks. Conflict between word name and ink color produces a strong conscious
effort to inhibit saying the written word. |
|
1 |
| Posner; Constructing Neuronal Theories |
190 |
|
Relation between vigilance system and awareness. |
|
0 |
| Posner; Constructing Neuronal Theories |
190 |
|
When a person attends to a source of sensory input in order to detect an infrequent target, the subjective
feeling is up emptying
the head of thoughts or feelings. |
|
0 |
| Posner; Constructing Neuronal Theories |
190 |
|
Subjective "clearing
of consciousness" appears to be accompanied
by an
increase in activation of the right frontal lobe vigilance network and a reduction in the anterior cingulate. |
|
0 |
| Posner; Constructing Neuronal Theories |
190 |
|
Feelings of effort associated with target detection or inhibiting prepotent responses are accompanied by evidence of cingulate
activation. |
|
0 |
| Posner; Constructing Neuronal Theories |
190 |
|
Clearing of thought is accompanied by evidence of cingulate
inhibition. |
|
0 |
| Posner; Constructing Neuronal Theories |
190 |
|
PET studies have
revealed important anatomical aspects of word reading. |
|
0 |
| Posner; Constructing Neuronal Theories |
190 |
|
The right
posterior temporal parietal area, activated both
by both consonants strings and words, is thought to be a visual
representation that is prelexical. |
|
0 |
| Posner; Constructing Neuronal Theories |
190 |
|
The left
ventral occipital area is involved in "visual word form," a
representation of the orthography of the letter string in which the individual letters are combined into a single chunk. |
|
0 |
| Posner; Constructing Neuronal Theories |
191 |
|
PET studies imply that letter strings are represented within the visual system both as unorganized features or letters and within a unified
visual word form. |
|
1 |
| Posner; Constructing Neuronal Theories |
191 |
|
When people attend
to color, motion, or form, appropriate posterior
prestriate areas are increased
in activation. |
|
0 |
| Posner; Constructing Neuronal Theories |
191 |
|
Attention
appears to amplify the activity of anatomical
areas in which the related computations occur. |
|
0 |
| Posner; Constructing Neuronal Theories |
191 |
|
Studies show a very strong posterior tempoparietal asymmetry in which electrical activity at about 100 ms is larger from the right hemisphere than from the left. |
|
0 |
| Posner; Constructing Neuronal Theories |
191 |
|
Study results fit the idea of
the right posterior generator related to visual
features
occurring within the first 100 ms. |
|
0 |
| Posner; Constructing Neuronal Theories |
191 |
|
Study results suggest that when attending to features, people search a representation located in the right posterior
temporal lobe. |
|
0 |
| Posner; Constructing Neuronal Theories |
192 |
|
PET studies show that the left frontal area is active when subjects deal with the meaning
of a word. |
|
1 |
| Posner; Constructing Neuronal Theories |
192 |
|
When the task requires association of several words to a given input, the
left frontal area is
joined by activation
in Wernicke's area. |
|
0 |
| Posner; Constructing Neuronal Theories |
192 |
|
If attention serves to amplify computations, it should be
possible to see amplified waveforms in the right posterior area in feature analysis and in the left frontal area and semantics. |
|
0 |
| Posner; Constructing Neuronal Theories |
192 |
|
Research results show that the left frontal area was more active at about 200-300 ms when the task was semantic, while the right
posterior area was more active when the task was feature search. |
|
0 |
| Posner; Constructing Neuronal Theories of Mind |
193 |
|
Reentrant signaling establishes correlations between cortical maps, within or
between different levels of the nervous system. |
|
1 |
| Posner; Constructing Neuronal Theories of Mind |
193 |
|
Visual computation occurs at 100 ms, followed by semantic computation, which might
be complete by 200-300 ms. |
|
0 |
| Posner; Constructing Neuronal Theories of Mind |
193 |
|
The area
making a semantic
computation was amplified in electrical activity of about 100
ms after the initial
computation. |
|
0 |
| Posner; Constructing Neuronal Theories of Mind |
194 |
|
Attention amplifies
computations
within particular
areas,
but does so by reentering the area, not by amplifying its initial activation. |
|
1 |
| Posner; Constructing Neuronal Theories of Mind |
195 |
|
Anterior cingulate connections to limbic, thalamic, and basal ganglia pathways distributes
frontal network activity to the widely
dispersed connections
involved in cognitive computations. |
|
1 |
| Posner; Constructing Neuronal Theories of Mind |
195 |
|
The posterior
attention network (including the parietal lobe and associated thalamic and midbrain areas) and the anterior
attention network (including the anterior cingulate) influence each other via direct cortical projections, but also indirectly through a comparator operation involving the
basal ganglia. |
|
0 |
| Posner; Constructing Neuronal Theories of Mind |
195 |
|
A sensory
event facilitates processing at a location due to
activation of the posterior network, but an expectation also operates via the anterior
network to facilitate
the expected location. |
|
0 |
| Posner; Constructing Neuronal Theories of Mind |
195 |
|
In the
basal ganglia loops, a direct
pathway between the anterior
cingulate and striatum serves as a reverberating
circuit to maintain
expected locations and amplify
them when their locations
match. |
|
0 |
| Posner; Constructing Neuronal Theories of Mind |
197 |
|
The distributed connections by which the attention systems assume control over
various functions
may develop over a considerable
period of life. |
|
2 |
| Posner; Constructing Neuronal Theories of Mind |
197 |
|
Elementary
mental operations are localized in discrete neural areas. |
|
0 |
| Posner; Constructing Neuronal Theories of Mind |
198 |
|
Cognitive tasks are performed by
a network of widely
distributed neural systems. |
|
1 |
| Posner; Constructing Neuronal Theories of Mind |
198 |
|
Computations
in a network interact by means of "reentrant"
processes. |
|
0 |
| Posner; Constructing Neuronal Theories of Mind |
198 |
|
Orderings
of computations is necessary for performance. Ordering does not take place by a strict serial organization. Instead, computations pass information back and forth to coordinate their results. |
|
0 |
| Posner; Constructing Neuronal Theories of Mind |
198 |
|
Precise connections exist between anatomically distant areas. A particular anatomical area is active whenever its computation is required. Since computations are often contingent on information from another area, information is fed back to reenter the critical areas. |
|
0 |
| Posner; Constructing Neuronal Theories of Mind |
198 |
|
Hierarchical control is a
property of network operation. Discovery of a separate network of anatomical
areas devoted to attention provides a basis for establishing executive
control over widely distributed networks. |
|
0 |
| Posner; Constructing Neuronal Theories of Mind |
198 |
|
Research results support the
idea of executive control by attention systems. |
|
0 |
| Posner; Constructing Neuronal Theories of Mind |
198 |
|
Activation of a computation produces a temporary reduction in the threshold for its reactivation. This principle underlies the cognitive phenomenon of priming. |
|
0 |
| Posner; Constructing Neuronal Theories of Mind |
198 |
|
For the
processing of words, priming exists at the level of attributes, word forms, phonology, and semantics. |
|
0 |
| Posner; Constructing Neuronal Theories of Mind |
198 |
|
When a computation is repeated, it's reduced threshold is accompanied
by reduced effort and
less attention. |
|
0 |
| Posner; Constructing Neuronal Theories of Mind |
199 |
|
Activating a computation from sensory input (bottom-up) and from attention (top-down) involves many
of the same neurons. |
|
1 |
| Posner; Constructing Neuronal Theories of Mind |
199 |
|
Practice in
the performance of any computation will decrease the neural networks necessary to
perform it. |
|
0 |
| Singer; Temporal Correlations in Neocortical Processing |
201 |
|
Putative Functions of Temporal
Correlations in Neocortical Processing |
|
2 |
| Singer; Temporal Correlations in Neocortical Processing |
201 |
|
Cells have
been found those responses distinguish between familiar and unfamiliar objects, are selective for particular aspects of faces, reflect precisely the location of a remembered target, or predict
with accuracy the direction of an eye movement. |
|
0 |
| Singer; Temporal Correlations in Neocortical Processing |
201 |
|
A particular
neuronal state would have to take into account not only the rate and specificity of individual neuron responses but also the relations between discharges of distributed neurons. |
|
0 |
| Singer; Temporal Correlations in Neocortical Processing |
204 |
|
Cells
occupying higher levels
in the processing
hierarchy tend to be selective for more complex constellations
of features than cells at lower levels. |
|
3 |
| Singer; Temporal Correlations in Neocortical Processing |
205 |
|
Representations consist of assemblies of a large number of simultaneously active neurons that may be
contained both in a single cortical area and also distributed over many cortical areas. |
|
1 |
| Singer; Temporal Correlations in Neocortical Processing |
205 |
|
The essential
feature of assembly
coding is that individual cells can participate at different
times in the representation of different objects. |
|
0 |
| Singer; Temporal Correlations in Neocortical Processing |
207 |
|
The formation of coherently active assemblies can
serve to enhance the saliency of responses to features that can be associated in a "meaningful" way. |
|
2 |
| Singer; Temporal Correlations in Neocortical Processing |
207 |
|
The concept of "binding by synchrony"
has been applied to intermodal integration and even to high-level processes underlying phenomena such as attention and consciousness. |
|
0 |
| Singer; Temporal Correlations in Neocortical Processing |
212 |
|
The hypothesis of temporally coded assemblies
requires that the probabilities with which distributed
cells synchronize their responses should reflect some of the Gestalt
criteria applied in perceptual
grouping. |
|
5 |
| Singer; Temporal Correlations in Neocortical Processing |
212 |
|
Synchronization probability within a particular cortical area
decreases with increasing distance between the
cells.
If the cells
are so closely spaced that
their receptive fields overlap, the probability is high that their responses will exhibit synchronous epochs if invoked with a single stimulus. |
|
0 |
| Singer; Temporal Correlations in Neocortical Processing |
213 |
|
Synchronization
probability appears to
reflect rather well some
of the gestalt
criteria for perceptual
grouping. |
|
1 |
| Singer; Temporal Correlations in Neocortical Processing |
215 |
|
Interactions
between distributed cell groups were found to be highly dynamic,
variable, and strongly influenced by the constellation of features in the visual stimulus. |
|
2 |
| Singer; Temporal Correlations in Neocortical Processing |
217 |
|
Synchronization
of responses can occur over considerable distances and between cell groups located in different cortical areas and even
hemispheres. |
|
2 |
| Singer; Temporal Correlations in Neocortical Processing |
217 |
|
Because response
synchronization occurred often in association
with oscillatory activity in the range of 30-60 Hz, it has been proposed that the observed synchronization phenomena in the visual cortex are due to common oscillatory input from subcortical centers. |
|
0 |
| Singer; Temporal Correlations in Neocortical Processing |
217 |
|
Oscillatory activity in the 30-60 Hz range has been described both for retinal ganglion cells and thalamic neurons. |
|
0 |
| Singer; Temporal Correlations in Neocortical Processing |
218 |
|
Thalamic oscillations are backpropagated from cortex by the corticothalamic projections. |
|
1 |
| Singer; Temporal Correlations in Neocortical Processing |
218 |
|
Large-scale synchronization of distributed thalamic neurons is common during sleep spindles, but correlated 30-60 Hz oscillatory activity has been observed only between closely
spaced cells. |
|
0 |
| Singer; Temporal Correlations in Neocortical Processing |
219 |
|
In mammals, corticocortical connections develop mainly postnatally and attain their final specificity through an activity-dependent selection process. |
|
1 |
| Singer; Temporal Correlations in Neocortical Processing |
227 |
|
There is ample evidence from brain structures other than the
visual cortex that groups of cells engage in synchronous rhythmic activity in the gamma frequency range. |
|
8 |
| Singer; Temporal Correlations in Neocortical Processing |
227 |
|
The fact that gamma activity occurs in the awake brain and increases with attention and preparation of motor
acts suggests
that it is functionally relevant. |
|
0 |
| Singer; Temporal Correlations in Neocortical Processing |
229 |
|
Neuronal networks that have been shaped extensively by prior
learning processes can settle very rapidly into a coherent state when the patterns of afferent sensory activity match |
|
2 |
| Singer; Temporal Correlations in Neocortical Processing |
233 |
|
Shifting attention by top-down processes would be
equivalent with biasing synchronization
probability of neurons
at lower levels by feedback connections from higher levels. |
|
4 |
| Singer; Temporal Correlations in Neocortical Processing |
236 |
|
The process of organizing the neuronal representation
consists of parallel operations that occurr
nearly simultaneously at different levels of the processing hierarchy and according to similar rules. |
|
3 |
| Stevens; Cortical Theory |
239 |
|
with the architecture of the weighted connections in the network. |
|
3 |
| Stevens; Cortical Theory |
239 |
|
Many functionally
distinct cortical regions, over 30 in the visual
system. |
|
0 |
| Stevens; Cortical Theory |
240 |
|
Functionally distinct cortical
regions, like V1 and MT,
might perform identical
mathematical operations on different sorts of inputs. [Bayesian
inference] |
|
1 |
| Stevens;
Cortical Theory |
240 |
|
Activity-dependent rewiring of cortical circuits could modify the computations
performed by even initially uniform cortices. The
character of some mathematical operation might vary continuously across even an apparently uniform cortical region like the
primary visual cortex. [Bayesian
inference] |
|
0 |
| Stevens; Cortical Theory |
240 |
|
How many inputs and outputs are present in cortex? The answer depends
on how many types of neurons are present.
Estimates indicate that the number of
Input and output neuron types should not a large
number, perhaps 10 to 100. |
|
0 |
| Stevens;
Cortical Theory |
240 |
|
Synaptic transmission is a stochastic
process. Neurotransmitter is released at axon terminals in packets—called quanta—so
that the total effect of a nerve impulse arrival is an integral multiple of
the smallest effect, the one produced by a single quantum. The quanta are released probabilistically
according to a Poisson process. |
|
0 |
| Stevens; Cortical Theory |
241 |
|
Probability of release of a packet quantum at an individual synapse is generally very low, about 0.1 to 0.5. |
|
1 |
| Stevens; Cortical Theory |
241 |
|
Any particular neuron generally seems to receive only one or two synapses from any other neuron. |
|
0 |
| Stevens; Cortical Theory |
241 |
|
In hippocampus, it has been estimated
that a given axon usually makes only a single synapse (average
estimated to be 1.3) on its target cell. |
|
0 |
| Stevens; Cortical Theory |
241 |
|
Lateral geniculate axons that project to visual cortex make
only one or a few (up to about eight) synapses on their targets. |
|
0 |
| Stevens; Cortical Theory |
241 |
|
When a pair
of cells is connected, the communication link between them is
quite unreliable for pulse arrival, although it is predictable
in a statistical sense. |
|
0 |
| Stevens; Cortical Theory |
241 |
|
The effect
of one neuron on another
is generally small and uncertain. |
|
0 |
| Stevens; Cortical Theory |
241 |
|
A single
input has only a relatively
small effect on its
target. |
|
0 |
| Stevens; Cortical Theory |
241 |
|
The random nature of synaptic transmission makes neuronal behavior uncertain;
networks of neurons must be described probabilistically. |
|
0 |
| Stevens; Cortical Theory |
242 |
|
Probabilistic descriptions are not
required for all neurons
in the brain. For Purkinje cells in the cerebellum, for example, in which one neuron
makes thousands of synapses on its target cell, statistical fluctuations in
synaptic strength are very
small. |
|
1 |
| Stevens; Cortical Theory |
242 |
|
A cubic
millimeter of cortex—a good candidate for the size of a computational unit —
contains 105 neurons, 109 synapses. |
|
0 |
| Stevens; Cortical Theory |
242 |
|
Each neuron
receives about 104 synapses and communicates with about 104 other neurons. |
|
0 |
| Stevens; Cortical Theory |
242 |
|
Most neuronal connections are intracortical. |
|
0 |
| Stevens; Cortical Theory |
242 |
|
Because single
neurons have small and
uncertain effects on other
neurons, the cortical description must be carried
out in terms of neuronal populations rather than at the level of individual cells. |
|
0 |
| Stevens; Cortical Theory |
242 |
|
Layer 4 neurons have a dendritic tree with a diameter of about 0.3 mm. |
|
0 |
| Stevens; Cortical Theory |
242 |
|
Layer 4 is
about 0.3 mm thick, and cortex has a density of about
105 neurons per mm3. |
|
0 |
| Stevens;
Cortical Theory |
242 |
|
All of the neurons in layer 4
that fall within a cylinder having a radius of about 0.3 mm will have overlapping dendritic trees. The number of neurons that overlap is
estimated to be approximately 8000. A significant
fraction of this population of neurons should
represent essentially the same information. |
|
0 |
| Stevens; Cortical Theory |
242 |
|
A given axon generally arborizes over a considerable region of cortex with an arbor diameter of perhaps 0.5 mm, and forms about 2000 boutons, each of which makes one or two
synapses. |
|
0 |
| Stevens; Cortical Theory |
243 |
|
Neurons of
the same functional class and in the same cortical layer share nearly the same potential
synaptic inputs whenever their cell bodies are separated by several hundred microns or less, and the degree of similarity in
their inputs increases as the distance between cell bodies decreases. |
|
1 |
| Stevens; Cortical Theory |
243 |
|
The overall stochastic
nature of neuronal behavior suggests that the physiologically
meaningful signal from cortex should be the average firing rates of a population of perhaps 100 to 1000 neurons near a particular cortical site. |
|
0 |
| Stevens;
Cortical Theory |
243 |
|
The behavior
of cortex at a particular
point is described by the firing in a population of neurons. The total firing that represents this population would be
determined by a weighted average of the appropriate neurons in the cortical region that
surrounded the point, perhaps with weights that are described by a spatial Gaussian. Moving from one
cortical location to an adjacent one, the variables describing cortical state
would vary continuously with cortical position. |
|
0 |
| Stevens; Cortical Theory |
243 |
|
A theory of cortex must be
coarse-grained and treat cortical inputs and outputs as continuous variables that represent the summed behavior of appropriately sized and selected neuron populations. |
|
0 |
| Stevens;
Cortical Theory |
243 |
|
The prominent
recurrent nature of lateral
intracortical connections and relatively wide
spatial distribution of cortical inputs mean that the cortical output at any one location
must depend on both the input and output over relatively great expanses of cortex. That is, the output
at any one point must be a functional, of both inputs and outputs. |
|
0 |
| Ullman; Sequence Seeking Counterstreams |
257 |
|
Sequence Seeking Counterstreams |
|
14 |
| Ullman; Sequence Seeking Counterstreams |
257 |
|
It would take an expert to
distinguish rat frontal cortex from sheep parietal cortex, or cat auditory
cortex from monkey somatosensory cortex. |
|
0 |
| Ullman; Sequence Seeking Counterstreams |
257 |
|
In visual
recognition, the task involves establishing a connection between
an incoming pattern and stored object representations in visual memory.
[recursion] [Bayesian
inference] [Fuster's perception-action cycle] |
|
0 |
| Ullman; Sequence Seeking Counterstreams |
257 |
|
Visual input
is processed through a sequence
of stages that includes edge detection, feature
extraction of varying complexity, and normalization
for size, position, and orientation. The
resulting neural representation is then compared with memory objects. [recursion]
[Bayesian inference]
[Fuster's perception-action
cycle] |
|
0 |
| Ullman; Sequence Seeking Counterstreams |
258 |
|
An attractive model for mental object search and matching
is to apply bidirectional methods, using both bottom-up and top-down processing. This counterstreams notion fits well with the 1-to-6
layered architecture of the cortex. [recursion]
[Bayesian inference]
[Fuster's perception-action
cycle] |
|
1 |
| Ullman; Sequence Seeking Counterstreams |
264 |
|
Planning motor actions can be implemented in terms of a sequence of movement trajectories
based on a stored repertoire of elementary movements. (FAPs) These basic movements can then be transformed and concatenated together to generate more complex movements. [Stereotyped motor
programs] [FAPs] |
|
6 |
| Ullman; Sequence Seeking Counterstreams |
264 |
|
The sequence-seeking
model requires two streams
going in opposite directions with the appropriate
cross-connections. The
counterstreams go up and down between layers 1 and 6 of the cortex, with
lateral cross connections between nearby areas. [recursion] [Bayesian inference] [Fuster's
perception-action cycle] |
|
0 |
| Ullman; Sequence Seeking Counterstreams |
264 |
|
The ascending
stream goes through layer
4 to a subpopulation
of the superficial layers, and then projects to layer 4 of the next cortical area. |
|
0 |
| Ullman; Sequence Seeking Counterstreams |
264 |
|
The descending
stream goes through a
different subpopulation
of the superficial layers to a descending
subpopulation of the infragranular
layers (often in layer 6), and from there to descending superficial layers of a preceding
area. |
|
0 |
| Ullman; Sequence Seeking Counterstreams |
265 |
|
Layer 5 (or
parts of it) may be involved in control functions. |
|
1 |
| Ullman; Sequence Seeking Counterstreams |
265 |
|
Layer 5's orderly connections to subcortical structures (e.g., from visual cortex to the pulvinar and the superior colliculus, structures implicated in controlling
attention and eye movements) that are reciprocally connected in a topographic manner to multiple visual areas. |
|
0 |
| Ullman; Sequence Seeking Counterstreams |
265 |
|
Firing pattern of a population of pyramidal cells in Layer 5 can initiate synchronized rhythms and project them on neurons in all layers. |
|
0 |
| Ullman; Sequence Seeking Counterstreams |
265 |
|
A separation between the ascending and
descending populations is evident in the
connections involving layer 4: the ascending streams terminate
in layer 4, the descending
streams always avoid it. In the superficial
layers the situation is more difficult to assess. |
|
0 |
| Ullman; Sequence Seeking Counterstreams |
267 |
|
In the magnocellular
projection from V1 to
V2, the forward projection originated mainly in
4B, while the back projection in mainly other layers (2b). |
|
2 |
| Ullman; Sequence Seeking Counterstreams |
268 |
|
Connections
between cortical areas can be classified as forward, backward, or lateral connections on the basis of the
laminar distribution of their source and destination. Lateral connections terminate in all layers. |
|
1 |
| Ullman; Sequence Seeking Counterstreams |
270 |
|
Counterstreams sequence-seeking
model is a bidirectional search performed by top-down and bottom-up streams seeking to meet. |
|
2 |
| Ullman; Sequence Seeking Counterstreams |
270 |
|
The counterstreams
functional architecture accounts for several
basic features of cortical circuitry: the predominantly reciprocal connectivity between
cortical areas; the forward,
backward, and lateral connection types; the regularities in the distribution patterns of interarea connections; the organization in 5-6 main
layers; the effects of back
projections. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
271 |
|
Dynamic Routing Strategies |
|
1 |
| Van
Essen; Dynamic Routing Strategies |
272 |
|
Ability to recognize a wide range of highly complex
patterns (e.g. faces) is relegated to a small number
of modules situated at high
levels of the visual hierarchy in inferotemporal cortex. |
|
1 |
| Van
Essen; Dynamic Routing Strategies |
272 |
|
Visual attention is a mechanism for dynamically regulating information
flow so as to bring information
from the visual field into an appropriate format
for the high-level object recognition center. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
272 |
|
Attention
can be directed to different locations and to different spatial scales. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
272 |
|
Attention shifts can be initiated by bottom-up cues and/or top-down influences. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
272 |
|
When initiated by bottom-up cues, attentional shifts occur with a finite temporal delay
(50-100 ms) and tend to persist in any given
location for a relatively
brief period.
In this respect, they are analogous to saccadic eye movements, except
they occur on a faster time scale. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
273 |
|
Attention
is directed not simply to the initial cue, but to whatever image
data lie within the window of attention once it has been shifted. |
|
1 |
| Van
Essen; Dynamic Routing Strategies |
273 |
|
Visual attention acts as an informational
bottleneck that reduces
to manageable levels the amount of image data reaching
high-level cortical centers involved in pattern recognition. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
273 |
|
For complex
patterns to be recognized, it is important that information
about spatial relationships be preserved within the window of
attention. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
274 |
|
Motor system
is capable of selecting among a large repertoire of stereotyped motor routines. [Stereotyped motor programs] [FAPs] |
|
1 |
| Van
Essen; Dynamic Routing Strategies |
274 |
|
Bottom-up sensory
cues as well as the top-down cognitive control. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
275 |
|
Neurobiologically plausible
mechanism for shifting and rescaling the representation of an object from the retinal reference frame into an object-centered reference frame. |
|
1 |
| Van
Essen; Dynamic Routing Strategies |
275 |
|
Information in the retinal reference frame is represented on a neural map (for instance, the topographic
representation in V1). |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
275 |
|
Hypothesize that information in
the object-centered reference
frame is also represented on a neural map that preserves some
degree of information about local spatial relationships. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
275 |
|
Each sample node in the high level map may be thought of as a feature vector representing various local image properties (such as orientation, texture, and depth). |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
276 |
|
Efficacy of
transmission of cortical
pathways is modulated by the
activity of control
neurons whose primary functionality is to dynamically route
information through successive
stages of the cortical
hierarchy. |
|
1 |
| Van
Essen; Dynamic Routing Strategies |
278 |
|
Purpose of attention is to focus the neural resources for recognition on a specific region within a scene. |
|
2 |
| Van
Essen; Dynamic Routing Strategies |
278 |
|
Salient areas
of a scene can often be defined
on the basis of
relatively low-level cues such as pop-out due to motion, depth, texture, or color. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
284 |
|
Major visual
processing pathways of the primate brain. Information from
the retinogeniculostriate pathway enters the visual
cortex through area V1 in the occipital lobe and proceeds through
a hierarchy of visual areas that can be subdivided into two major functional streams. |
|
6 |
| Van
Essen; Dynamic Routing Strategies |
284 |
|
The "form"
pathway leads ventrally through V4 and
inferotemporal cortex (IT) and is mainly
concerned with object identification, regardless of position or size. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
285 |
|
The "where"
pathway leads dorsally
into the posterior parietal complex, and is concerned with the locations
and spatial
relationships among objects, regardless of their
identity. |
|
1 |
| Van
Essen; Dynamic Routing Strategies |
285 |
|
Pulvinar, a
subcortical nucleus of the thalamus, makes reciprocal connections with all of
the visual processing cortical areas. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
285 |
|
V1 has
about twice the
density of neurons per unit surface area as the rest of neocortex. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
285 |
|
Model of attentional processing
in visual cortex. Different stages of the network correspond to the major
cortical areas in the "form" pathway. Two stages for V1: V1a
corresponding to layer 4C, and V1b corresponding to superficial layers. Remaining
areas—V2, V4, and inferotemporal cortex (IT)— occupy one stage apiece. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
285 |
|
Each node of
the attentional processing model corresponds to a
feature vector that represents
the activity profile of a large group (hundreds or thousands) of neurons in each visual area. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
287 |
|
Neural resources in IT
are probably devoted to recognition rather than representing the
contents of the window of attention itself. |
|
2 |
| Van
Essen; Dynamic Routing Strategies |
287 |
|
Hypothesize that the pulvinar plays an important role in providing the control signals required for the routing circuit of attentional
control. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
287 |
|
Pulvinar is
reciprocally connected
to all areas in the form pathway, making it a plausible candidate for modulating information flow from V1 to IT. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
287 |
|
Pulvinar
receives projections from both posterior
parietal cortex and superior colliculus, which are known to encode the direction of saccade targets and may also be involved in setting up attentional targets. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
287 |
|
Neurophysiological studies,
lesion studies, and neuroimaging studies of the pulvinar, suggest that it plays an important
role in visual attention. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
287 |
|
Pulvinar is
spatially localized
while at the same time able to communicate with vast areas of the visual cortex. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
287 |
|
Relative proximity of pulvinar neurons to each other could facilitate the competitive and cooperative interactions among the control neurons that are necessary to enforce the
constraint of having a single
window of attention. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
287 |
|
Intrapulvinar communication could possibly be subserved by interneurons within the pulvinar or through the
reticular nucleus of
the thalamus. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
288 |
|
Neural gating
mechanisms are believed to play an important role
in many aspects of nervous system function. |
|
1 |
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Essen; Dynamic Routing Strategies |
288 |
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A pyramidal
neuron may branch to several cortical areas and make synaptic connections to a multitude of neurons. |
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0 |
| Van
Essen; Dynamic Routing Strategies |
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Dynamic routing model predicts that the receptive field of cortical
neurons should change their position or size as attention is shifted or rescaled. |
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| Van
Essen; Dynamic Routing Strategies |
293 |
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Synchrony
of neural firing could
serve as a code for linking features common to a given object. |
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4 |
| Van
Essen; Dynamic Routing Strategies |
293 |
|
Temporal information might be used to
solve the "binding problem" and thereby mediate aspects of
figure/ground segregation, attention, and perhaps even consciousness. |
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0 |
| Van
Essen; Dynamic Routing Strategies |
294 |
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Ullman has
proposed that pattern
recognition is achieved by an "counterstreams" strategy, in which information
about stored patterns flows top-down at the same time that information about currently viewed patterns flows in the bottom-up direction. [recursion]
[Bayesian inference]
[Fuster's perception-action
cycle] |
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| Van
Essen; Dynamic Routing Strategies |
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Ullman's counterstreams
strategy involves multiple
coexisting representations that flow in each direction, and recognition is manifested by a winner-take-all computation to find the best match between patterns propagating in the two directions. [recursion]
[Bayesian inference]
[Fuster's perception-action
cycle] |
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0 |
| Van
Essen; Dynamic Routing Strategies |
296 |
|
Brain's motor
system includes cerebellum as well as cerebral cortical areas and numerous subcortical nuclei in the forebrain (basal ganglia), thalamus, midbrain, and brainstem. |
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2 |
| Van
Essen; Dynamic Routing Strategies |
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|
Each neuron "votes" for a particular direction of
movement that it influences, and the strength
of its vote is proportional to its firing rate. |
|
0 |
| Van
Essen; Dynamic Routing Strategies |
297 |
|
To have a particular
digit or other appendage execute movement, the stereotyped
spatiotemporal pattern would be selectively routed into the neural populations in motor cortex that control the relevant digits. [Stereotyped motor programs] [FAPs] |
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1 |
| Van
Essen; Dynamic Routing Strategies |
297 |
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Representation
of each digit or other appendage is likely to be an overlapping and interleaved ensembles of neurons. |
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0 |
| Van
Essen; Dynamic Routing Strategies |
297 |
|
Information
about a motor routine might be communicated
indirectly between cortical areas via the well-known
route involving the basal ganglia and thalamus, rather than via direct corticocortical connections. |
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0 |
| Van
Essen; Dynamic Routing Strategies |
297 |
|
Thalamic motor nuclei (VA and the VL) terminate mainly in the middle layers of motor cortex. |
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0 |
| Van
Essen; Dynamic Routing Strategies |
299 |
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Multiplicative
operations whereby "control
neurons" dynamically modulate the connection between
two other groups of neurons. |
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2 |
| Van
Essen; Dynamic Routing Strategies |
299 |
|
Complex nonlinearities have been introduced to achieve flexibility
in neural
computational systems using dynamic links or oscillations. |
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0 |
| Van
Essen; Dynamic Routing Strategies |
299 |
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Distinguish control
functions from information
flow and processing. |
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0 |
| Van
Essen; Dynamic Routing Strategies |
299 |
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Three-way interactions provide a
contextual framework for modifying the interpretation of information, which
is an essential ingredient for cognitive processing. |
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0 |
| Van
Essen; Dynamic Routing Strategies |
299 |
|
Hierarchical interpretative
systems |
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0 |
| Van
Essen; Dynamic Routing Strategies |
299 |
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Complex circuits requires physical structure to be largely laid down by genetic
factors. |
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0 |
| Van
Essen; Dynamic Routing Strategies |
299 |
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Well-defined structure for the
neocortex and its connections to subcortical bodies that is replicated across
individuals and not
modified on a gross scale by experience. |
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0 |
| Van
Essen; Dynamic Routing Strategies |
299 |
|
Whereas the details on the information about complex
objects contained within the inferotemporal cortex differs between individuals, the strategies for acquiring that information, and the way it is stored and retrieved, is
presumed to be very similar. |
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