scholarly journals Efficient sampling and noisy decisions

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Joseph A Heng ◽  
Michael Woodford ◽  
Rafael Polania
Keyword(s):  
Cognitive Processes ◽  
Information Coding ◽  
Optimal Process ◽  
Environmental Distribution ◽  
Numerosity Discrimination ◽  
Efficient Coding ◽  
Decision Systems ◽  
Sampling Process ◽  
Efficient Sampling ◽  
Full Adaptation

Human decisions are based on finite information, which makes them inherently imprecise. But what determines the degree of such imprecision? Here, we develop an efficient coding framework for higher-level cognitive processes in which information is represented by a finite number of discrete samples. We characterize the sampling process that maximizes perceptual accuracy or fitness under the often-adopted assumption that full adaptation to an environmental distribution is possible, and show how the optimal process differs when detailed information about the current contextual distribution is costly. We tested this theory on a numerosity discrimination task, and found that humans efficiently adapt to contextual distributions, but in the way predicted by the model in which people must economize on environmental information. Thus, understanding decision behavior requires that we account for biological restrictions on information coding, challenging the often-adopted assumption of precise prior knowledge in higher-level decision systems.

scholarly journals Efficient sampling and noisy decisions

2019 ◽  
Author(s):  
Joseph Heng ◽  
Michael Woodford ◽  
Rafael Polania
Keyword(s):  
Cognitive Processes ◽  
Information Coding ◽  
Optimal Process ◽  
Environmental Distribution ◽  
Numerosity Discrimination ◽  
Efficient Coding ◽  
Decision Systems ◽  
Sampling Process ◽  
Efficient Sampling ◽  
Full Adaptation

AbstractThe precision of human decisions is limited by both processing noise and basing decisions on finite information. But what determines the degree of such imprecision? Here we develop an efficient coding framework for higher-level cognitive processes, in which information is represented by a finite number of discrete samples. We characterize the sampling process that maximizes perceptual accuracy or fitness under the often-adopted assumption that full adaptation to an environmental distribution is possible, and show how the optimal process differs when detailed information about the current contextual distribution is costly. We tested this theory on a numerosity discrimination task, and found that humans efficiently adapt to contextual distributions, but in the way predicted by the model in which people must economize on environmental information. Thus, understanding decision behavior requires that we account for biological restrictions on information coding, challenging the often-adopted assumption of precise prior knowledge in higher-level decision systems.

scholarly journals Nonlinear convergence boosts information coding in circuits with parallel outputs

2019 ◽  
Author(s):  
Gabrielle J. Gutierrez ◽  
Fred Rieke ◽  
Eric T. Shea-Brown
Keyword(s):  
Nonlinear Response ◽  
Single Neuron ◽  
Neural Circuits ◽  
Response Functions ◽  
Information Coding ◽  
Efficient Coding ◽  
Coding Efficiency ◽  
Parallel Pathways ◽  
Simultaneous Impact ◽  
Circuit Structure

Neural circuits are structured with layers of converging and diverging connectivity, and selectivity-inducing nonlinearities at neurons and synapses. These components have the potential to hamper an accurate encoding of the circuit inputs. Past computational studies have optimized the nonlinearities of single neurons, or connection weights in networks, to maximize encoded information, but have not grappled with the simultaneous impact of convergent circuit structure and nonlinear response functions for efficient coding. Our approach is to compare model circuits with different combinations of convergence, divergence, and nonlinear neurons to discover how interactions between these components affect coding efficiency. We find that a convergent circuit with divergent parallel pathways can encode more information with nonlinear subunits than with linear subunits, despite the compressive loss induced by the convergence and the nonlinearities when considered individually. These results show that the combination of selective nonlinearities and a convergent architecture - both elements that reduce information when acting separately - can promote efficient coding.Significance StatementComputation in neural circuits relies on a common set of motifs, including divergence of common inputs to parallel pathways, convergence of multiple inputs to a single neuron, and nonlinearities that select some signals over others. Convergence and circuit nonlinearities, considered individually, can lead to a loss of information about inputs. Past work has detailed how optimized nonlinearities and circuit weights can maximize information, but here, we show that incorporating non-invertible nonlinearities into a circuit with divergence and convergence, can enhance encoded information despite the suboptimality of these components individually. This study extends a broad literature on efficient coding to convergent circuits. Our results suggest that neural circuits may preserve more information using suboptimal components than one might expect.

scholarly journals Metabolically Efficient Information Processing

2001 ◽  
Vol 13 (4) ◽  
pp. 799-815 ◽  
Author(s):  
Vijay Balasubramanian ◽  
Don Kimber ◽  
Michael J. Berry II
Keyword(s):  
Energy Efficient ◽  
Transmission Rate ◽  
Electronic Devices ◽  
Power Electronic ◽  
Information Coding ◽  
Power Constraint ◽  
Power Cost ◽  
Efficient Coding ◽  
Cost Constraints ◽  
Efficient Information

Energy-efficient information transmission may be relevant to biological sensory signal processing as well as to low-power electronic devices. We explore its consequences in two different regimes. In an “immediate” regime, we argue that the information rate should be maximized subject to a power constraint, and in an “exploratory” regime, the transmission rate per power cost should be maximized. In the absence of noise, discrete inputs are optimally encoded into Boltzmann distributed output symbols. In the exploratory regime, the partition function of this distribution is numerically equal to 1. The structure of the optimal code is strongly affected by noise in the transmission channel. The Arimoto-Blahut algorithm, generalized for cost constraints, can be used to derive and interpret the distribution of symbols for optimal energy-efficient coding in the presence of noise. We outline the possibilities and problems in extending our results to information coding and transmission in neurobiological systems.

scholarly journals Nonlinear convergence boosts information coding in circuits with parallel outputs

2021 ◽  
Vol 118 (8) ◽  
pp. e1921882118
Author(s):  
Gabrielle J. Gutierrez ◽  
Fred Rieke ◽  
Eric T. Shea-Brown
Keyword(s):  
Nonlinear Response ◽  
Neural Circuits ◽  
Computational Studies ◽  
Response Functions ◽  
Single Neurons ◽  
Information Coding ◽  
Efficient Coding ◽  
Coding Efficiency ◽  
Simultaneous Impact ◽  
Circuit Structure

Neural circuits are structured with layers of converging and diverging connectivity and selectivity-inducing nonlinearities at neurons and synapses. These components have the potential to hamper an accurate encoding of the circuit inputs. Past computational studies have optimized the nonlinearities of single neurons, or connection weights in networks, to maximize encoded information, but have not grappled with the simultaneous impact of convergent circuit structure and nonlinear response functions for efficient coding. Our approach is to compare model circuits with different combinations of convergence, divergence, and nonlinear neurons to discover how interactions between these components affect coding efficiency. We find that a convergent circuit with divergent parallel pathways can encode more information with nonlinear subunits than with linear subunits, despite the compressive loss induced by the convergence and the nonlinearities when considered separately.

Elaborating the role of reflection and individual differences in the study of folk-economic beliefs

2018 ◽  
Vol 41 ◽  
Author(s):  
Kevin Arceneaux
Keyword(s):  
Decision Making ◽  
Individual Differences ◽  
Cognitive Processes ◽  
Evolutionary History ◽  
Behavioral Responses ◽  
History Of ◽  
Economic Beliefs

AbstractIntuitions guide decision-making, and looking to the evolutionary history of humans illuminates why some behavioral responses are more intuitive than others. Yet a place remains for cognitive processes to second-guess intuitive responses – that is, to be reflective – and individual differences abound in automatic, intuitive processing as well.

A cognitive approach to cumulative technological culture is useful and necessary but only if it also applies to other species

2020 ◽  
Vol 43 ◽  
Author(s):  
Thibaud Gruber
Keyword(s):  
Social Learning ◽  
Cognitive Processes ◽  
Learning Processes ◽  
Cognitive Approach ◽  
Technological Culture ◽  
Social Learning Processes

Abstract The debate on cumulative technological culture (CTC) is dominated by social-learning discussions, at the expense of other cognitive processes, leading to flawed circular arguments. I welcome the authors' approach to decouple CTC from social-learning processes without minimizing their impact. Yet, this model will only be informative to understand the evolution of CTC if tested in other cultural species.

Reaction Time and Brain Waves in Omitted Stimulus Tasks

2010 ◽  
Vol 24 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Oscar H. Hernández ◽  
Muriel Vogel-Sprott
Keyword(s):  
Reaction Time ◽  
Cognitive Processes ◽  
Young Male ◽  
Event Related Potential ◽  
Auditory Stimuli ◽  
Motor Action ◽  
Cognitive Component ◽  
Sensory Modalities ◽  
Two Measures ◽  
Somatosensory Stimuli

A missing stimulus task requires an immediate response to the omission of a regular recurrent stimulus. The task evokes a subclass of event-related potential known as omitted stimulus potential (OSP), which reflects some cognitive processes such as expectancy. The behavioral response to a missing stimulus is referred to as omitted stimulus reaction time (RT). This total RT measure is known to include cognitive and motor components. The cognitive component (premotor RT) is measured by the time from the missing stimulus until the onset of motor action. The motor RT component is measured by the time from the onset of muscle action until the completion of the response. Previous research showed that RT is faster to auditory than to visual stimuli, and that the premotor of RT to a missing auditory stimulus is correlated with the duration of an OSP. Although this observation suggests that similar cognitive processes might underlie these two measures, no research has tested this possibility. If similar cognitive processes are involved in the premotor RT and OSP duration, these two measures should be correlated in visual and somatosensory modalities, and the premotor RT to missing auditory stimuli should be fastest. This hypothesis was tested in 17 young male volunteers who performed a missing stimulus task, who were presented with trains of auditory, visual, and somatosensory stimuli and the OSP and RT measures were recorded. The results showed that premotor RT and OSP duration were consistently related, and that both measures were shorter with respect to auditory stimuli than to visual or somatosensory stimuli. This provides the first evidence that the premotor RT is related to an attribute of the OSP in all three sensory modalities.

Do Event-Related Brain Potentials Reflect Mental (Cognitive) Operations?

2002 ◽  
Vol 16 (3) ◽  
pp. 129-149 ◽  
Author(s):  
Boris Kotchoubey
Keyword(s):  
Cognitive Processes ◽  
Point Of View ◽  
Internal Variables ◽  
Brain Potentials ◽  
Cognitive Operations ◽  
External Variables ◽  
Series Of Experiments ◽  
Mental Operations ◽  
A Chain ◽  
Processing Mechanisms

Abstract Most cognitive psychophysiological studies assume (1) that there is a chain of (partially overlapping) cognitive processes (processing stages, mechanisms, operators) leading from stimulus to response, and (2) that components of event-related brain potentials (ERPs) may be regarded as manifestations of these processing stages. What is usually discussed is which particular processing mechanisms are related to some particular component, but not whether such a relationship exists at all. Alternatively, from the point of view of noncognitive (e. g., “naturalistic”) theories of perception ERP components might be conceived of as correlates of extraction of the information from the experimental environment. In a series of experiments, the author attempted to separate these two accounts, i. e., internal variables like mental operations or cognitive parameters versus external variables like information content of stimulation. Whenever this separation could be performed, the latter factor proved to significantly affect ERP amplitudes, whereas the former did not. These data indicate that ERPs cannot be unequivocally linked to processing mechanisms postulated by cognitive models of perception. Therefore, they cannot be regarded as support for these models.

Inefficient Encoding as an Explanation for Age-Related Deficits in Recollection-Based Processing

2014 ◽  
Vol 28 (3) ◽  
pp. 148-161 ◽  
Author(s):  
David Friedman ◽  
Ray Johnson
Keyword(s):  
Older Adults ◽  
Young Adults ◽  
Cognitive Processes ◽  
Brain Activity ◽  
Memory Performance ◽  
Brain Regions ◽  
Semantic Retrieval ◽  
Age Related ◽  
The Face ◽  
Episodic Memories

A cardinal feature of aging is a decline in episodic memory (EM). Nevertheless, there is evidence that some older adults may be able to “compensate” for failures in recollection-based processing by recruiting brain regions and cognitive processes not normally recruited by the young. We review the evidence suggesting that age-related declines in EM performance and recollection-related brain activity (left-parietal EM effect; LPEM) are due to altered processing at encoding. We describe results from our laboratory on differences in encoding- and retrieval-related activity between young and older adults. We then show that, relative to the young, in older adults brain activity at encoding is reduced over a brain region believed to be crucial for successful semantic elaboration in a 400–1,400-ms interval (left inferior prefrontal cortex, LIPFC; Johnson, Nessler, & Friedman, 2013 ; Nessler, Friedman, Johnson, & Bersick, 2007 ; Nessler, Johnson, Bersick, & Friedman, 2006 ). This reduced brain activity is associated with diminished subsequent recognition-memory performance and the LPEM at retrieval. We provide evidence for this premise by demonstrating that disrupting encoding-related processes during this 400–1,400-ms interval in young adults affords causal support for the hypothesis that the reduction over LIPFC during encoding produces the hallmarks of an age-related EM deficit: normal semantic retrieval at encoding, reduced subsequent episodic recognition accuracy, free recall, and the LPEM. Finally, we show that the reduced LPEM in young adults is associated with “additional” brain activity over similar brain areas as those activated when older adults show deficient retrieval. Hence, rather than supporting the compensation hypothesis, these data are more consistent with the scaffolding hypothesis, in which the recruitment of additional cognitive processes is an adaptive response across the life span in the face of momentary increases in task demand due to poorly-encoded episodic memories.

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