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Cohen, J. D.

Publications and source records attributed to Cohen, J. D..

6 recordsLinked to original sources
bioRxiv2018

The Eighty Five Percent Rule for Optimal Learning

Researchers and educators have long wrestled with the question of how best to teach their clients be they human, animal or machine. Here we focus on the role of a single variable, the difficulty of training, and examine its effect on the rate of learning. In many situations we find that there is a sweet spot in which training is neither too easy nor too hard, and where learning progresses most quickly. We derive conditions for this sweet spot for a broad class of learning algorithms in the context of binary classification tasks, in which ambiguous stimuli must be sorted into one of two classes. For all of these gradient-descent based learning algorithms we find that the optimal error rate for training is around 15.87% or, conversely, that the optimal training accuracy is about 85%. We demonstrate the efficacy of this Eighty Five Percent Rule for artificial neural networks used in AI and biologically plausible neural networks thought to describe human and animal learning.

animal behavior and cognition↗
bioRxiv2018

A pupillary index of susceptibility to decision biases

Under what conditions do humans systematically deviate from rational decision making? Here we show that pupillary indices of low neural gain are associated with strong and consistent biases across six different extensively-studied decision making tasks, whereas indices of high gain are associated with weak or absent biases. Lower susceptibility to biases, however, comes at the cost of indecisiveness, or alternatively, prolonged deliberation time. We explain the association between low gain and strong biases as reflecting a broader information integration process that gives greater weight to weak biasing influences. The findings underscore the role of pupil-linked brain states in the generation of decision making biases.\n\nSignificance\"Framing effects\" are demonstrations that peoples decisions can be biased by the way a decision problem is presented, and consequently, people can make decisions that violate the principles of rationality. Using a set of classic decision-making tasks, we show that pupil dilation, previously linked to levels of the neuromodulator norepinephrine and to a tradeoff between narrowly focused and broadly integrative modes of information processing, distinguishes between people who are consistently biased and people who are relatively immune to these effects. Our findings suggest that norepinephrine may drive these individual differences, and that a narrowly focused mode of information processing confers relative immunity to these decision making biases, whereas the integration of a wider range of information results in greater susceptibility.

neuroscience↗
bioRxiv2017

Anomalous Diffusion as a Descriptive Model of Cell Migration

Appropriately chosen descriptive models of cell migration in biomaterials will allow researchers to characterize and ultimately predict the movement of cells in engineered systems for a variety of applications in tissue engineering. The persistent random walk (PRW) model accurately describes cell migration on two-dimensional (2D) substrates. However, this model inherently cannot describe subdiffusive cell movement, i.e. migration paths in which the root mean square displacement increases more slowly than the square root of the time interval. Subdiffusivity is a common characteristic of cells moving in confined environments, such as three-dimensional (3D) porous scaffolds, hydrogel networks, and in vivo tissues. We demonstrate that a generalized anomalous diffusion (AD) model, which uses a simple power law to relate the mean square displacement (MSD) to time, more accurately captures individual cell migration paths across a range of engineered 2D and 3D environments than does the more commonly used PRW model. We used the AD model parameters to distinguish cell movement profiles on substrates with different chemokinetic factors, geometries (2D vs 3D), substrate adhesivities, and compliances. Although the two models performed with equal precision for superdiffusive cells, we suggest a simple AD model, in lieu of PRW, to describe cell trajectories in populations with a significant subdiffusive fraction, such as cells in confined, 3D environments.

bioengineering↗
bioRxiv2017

Perceptual decisions result from the continuous accumulation of memory and sensory evidence

Expectations can inform fast, accurate decisions. But what informs expectations? Here we test the hypothesis that expectations are set by dynamic inference from memory. Participants performed a cue-guided perceptual decision task with independently-varying memory and sensory evidence. Cues established expectations by reminding participants of past stimulus-stimulus pairings, which predicted the likely target in a subsequent noisy image stream. Participants responses used both memory and sensory information, in accordance to their relative reliability. Formal model comparison showed that the sensory inference was best explained when its parameters were set dynamically at each trial by evidence sampled from memory. Supporting this model, neural pattern analysis revealed that responses to the probe were modulated by the specific content and fidelity of memory reinstatement that occurred before the probe appeared. Together, these results suggest that perceptual decisions arise from the continuous sampling of memory and sensory evidence.

neuroscience↗
bioRxiv2017

Dissociable neural mechanisms track evidence accumulation for selection of attention versus action

Decision-making is typically studied as a sequential process from the selection of what to attend (e.g., between possible tasks, stimuli, or stimulus attributes) to the selection of which actions to take based on the attended information. However, people often gather information across these levels in parallel. For instance, even as they choose their actions, they may continue to evaluate how much to attend other tasks or dimensions of information within a task. We scanned participants while they made such parallel evaluations, simultaneously weighing how much to attend two dynamic stimulus attributes and which response to give based on the attended information. Regions of prefrontal cortex tracked information about the stimulus attributes in dissociable ways, related to either the predicted reward (ventromedial prefrontal cortex) or the degree to which that attribute was being attended (dorsal anterior cingulate, dACC). Within dACC, adjacent regions tracked uncertainty at different levels of the decision, regarding what to attend versus how to respond. These findings bridge research on perceptual and value-based decision-making, demonstrating that people dynamically integrate information in parallel across different levels of decision making.\n\nNaturalistic decisions allow an individual to weigh their options within a particular task (e.g., how best to word the introduction to a paper) while also weighing how much to attend other tasks (e.g., responding to e-mails). These different types of decision-making have a hierarchical but reciprocal relationship: Decisions at higher levels inform the focus of attention at lower levels (e.g., whether to select between citations or email addresses) while, at the same time, information at lower levels (e.g., the salience of an incoming email) informs decisions regarding which task to attend. Critically, recent studies suggest that decisions across these levels may occur in parallel, continuously informed by information that is integrated from the environment and from ones internal milieu1,2.\n\nResearch on cognitive control and perceptual decision-making has examined how responses are selected when attentional targets are clearly defined (e.g., based on instruction to attend a stimulus dimension), including cases in which responding requires accumulating information regarding a noisy percept (e.g., evidence favoring a left or right response)3-7. Separate research on value-based decision-making has examined how individuals select which stimulus dimension(s) to attend in order to maximize their expected rewards8-11. However, it remains unclear how the accumulation of evidence to select high-level goals and/or attentional targets interacts with the simultaneous accumulation of evidence to select responses according to those goals (e.g., based on the perceptual properties of the stimuli). Recent work has highlighted the importance of such interactions to understanding task selection12-15, multi-attribute decision-making16-18, foraging behavior19-21, cognitive effort22,23, and self-control24-27.\n\nWhile these interactions remain poorly understood, previous research has identified candidate neural mechanisms associated with multi-attribute value-based decision-making11,28,29 and with selecting a response based on noisy information from an instructed attentional target3-5. These research areas have implicated the ventromedial prefrontal cortex (vmPFC) in tracking the value of potential targets of attention (e.g., stimulus attributes)8,11 and the dorsal anterior cingulate cortex (dACC) in tracking an individuals uncertainty regarding which response to select30-32. It has been further proposed that dACC may differentiate between uncertainty at each of these parallel levels of decision-making (e.g., at the level of task goals or strategies vs. specific motor actions), and that these may be separately encoded at different locations along the dACCs rostrocaudal axis32,33. However, neural activity within and across these prefrontal regions has not yet been examined in a setting in which information is weighed at both levels within and across trials.\n\nHere we use a value-based perceptual decision-making task to examine how people integrate different dynamic sources of information to decide (a) which perceptual attribute to attend and (b) how to respond based on the evidence for that attribute. Participants performed a task in which they regularly faced a conflict between attending the stimulus attribute that offered the greater reward or the attribute that was more perceptually salient (akin to persevering in writing ones paper when an enticing email awaits). We demonstrate that dACC and vmPFC track evidence for the two attributes in dissociable ways. Across these regions, vmPFC weighs attribute evidence by the reward it predicts and dACC weighs it by its attentional priority (i.e., the degree to which that attribute drives choice). Within dACC, adjacent regions differentiated between uncertainty at the two levels of the decision, regarding what to attend (rostral dACC) versus how to respond (caudal dACC).

neuroscience↗
bioRxiv2017

Refresh my memory: Episodic memory reinstatements intrude on working memory maintenance

A fundamental question in memory research is how different forms of memory interact. Previous research has shown that people rely on working memory (WM) in short-term recognition tasks; a common view is that episodic memory (EM) only influences performance on these tasks when WM maintenance is disrupted. However, retrieval of memories from EM has been widely observed during brief periods of quiescence, raising the possibility that EM retrievals during maintenance-critically, before a response can be prepared-might affect short-term recognition memory performance even in the absence of distraction. We hypothesized that this influence would be mediated by the lingering presence of reactivated EM content in WM. We obtained support for this hypothesis in three experiments, showing that delay-period EM reactivation introduces incidentally-associated information (context) into WM, and that these retrieved associations negatively impact subsequent recognition, leading to substitution errors (Experiment 1) and slowing of accurate responses (Experiment 2). fMRI pattern analysis showed that slowing is mediated by the content of EM reinstatement (Experiment 3). These results expose a previously hidden influence of EM on WM, raising new questions about the adaptive nature of their interaction.

animal behavior and cognition↗